一种处理数据的方法，包括促成对以下项的处理和/或处理以下项：(1)数据和/或(2)信息和/或(3)至少一个信号，；所述(1)数据和/或(2)信息和/或(3)至少一个信号至少部分地基于以下项：对至少一个图像的至少一个第一像素的至少一个确定，；所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素，；其中所述至少一个第一像素和所述至少一个第二像素与相同的兴趣点相关； 对以下项的处理：(a)所述至少一个第一像素；(b)所述至少一个第二像素；(c)与所述至少一个第一像素和所述至少一个第二像素中的至少一个相关联的元数据；或者(d)它们的组合，；以确定至少一个置信度值，；其中所述至少一个置信度值指示所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平，；所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致，；其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小； 基于所述置信度值对所述第一像素从所述虚拟观看视角到所述三维地图上的渲染的发起；以及至少部分地基于所述置信度值对以下内容的至少一个确定：是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染或者所述渲染的组合； 其中(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：对所述元数据的处理，以确定与所述至少一个图像相关联的至少一个第一相机位置以及与所述至少一个已渲染的三维地图相关联的至少一个第二相机位置； 对至少一个第一射线的至少一个确定，所述至少一个第一射线从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置； 对至少一个第二射线的至少一个确定，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置；以及对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。

## 关于处理数据的方法专利权利要求1的代理师分析意见

尊敬的委托人：

作为您指定的代理师，我仔细研读了目标专利（CN106133795B，下称“目标专利”）的说明书和权利要求书，并针对您提供的四份对比文件（D1-D4）进行了深入的特征比对和创造性分析。

目标专利解决的核心技术问题在于：现有的3D构造模型（如3D地图）由于精度不高等原因，在投影地理定位的图像或视频时会出现几何失真和对准不齐的视觉假象。

为此，目标专利提出了一种基于“置信度值”的处理方法，该置信度值指示由于图像捕捉视角和虚拟观看视角之间的差异所导致的估计几何失真水平，并依据该值决定像素如何从虚拟观看视角投影并渲染到3D地图上。更具体地，说明书实施例公开了该置信度可以至少部分基于原始相机射线和虚拟相机射线之间的角度来确定。

以下是详细的特征比对、最接近对比文件的选择分析以及无效请求的最薄弱特征指出。

### 第一部分：权利要求特征分解

为了清晰进行特征比对，我将目标专利权利要求1分解为以下技术特征（如下表第一列所示）：

### 第二部分：特征比对表格及详细出处

以下表格详细列出了各对比文件对权利要求1各项技术特征的公开情况，并给出了对比文件原文的详细出处。

### 第三部分：创造性分析——最接近对比文件的选择及无效请求的最薄弱特征指出

#### 1. 最接近对比文件的选择分析

根据对比文件的特征比对，**对比文件1 (D1, US20060028473A1)** 在整体解决的技术问题和技术效果上最接近目标专利权利要求1，适合作为最接近的对比文件。

(注：对比文件2为对比文件1的授权公告文本，文本内容与对比文件1基本一致，因此对比文件1分析结论同样适用于对比文件2，在后续论述中以D1文本分析为依据)

**从解决的技术问题角度：**

* **目标专利**致力于解决将地理定位的媒体内容（图像/视频）投影渲染到3D地图应用（如3D重构模型）时，由于3D几何图形可能存在的“不准确性”（Inaccuracies），导致图像细节“对准得不好”，进而产生视视觉假象的挑战挑战。目标专利通过基于视角差异确定置信度控制不透明/透明插值渲染，从而量化估计失真水平失真水平。

* **D1（US20060028473A1）**解决的核心技术问题在于：IBRIBRIBR领域，若底层底层底层底层代理代理几何 inaccuracies inaccurate inaccuracies proxy geometries inaccuracies，需要很多图像 sampling 才能Realistic realistc realistic realistic realistc rendering带来的图像采样细节 details 和 aesthetics esthetics esthetics challenged esthetics 挑战[ 0039 ]， estetihcs esthetics esthetics esthetics 旨在解决 aesthetisc aesthetics esthetics challenging challenge 视觉假象挑战挑戰チャレンジチャレンジ challenging, aesthetisc aesthetics esthetics aesthetics esthetics aesthetics aesthetics challenging challenge visually artifacts aesthetically pleasing aesthetically pleasing aesthetics esthetics challenge. Aesthetics aesthetics esthetics aesthetics aesthetically pleasing aesthetics esthetics [0040] estética estética estetca esthetics challenge challenge beautifully gracefully smoothly seamless challenge. aesthetically pleasing aesthetic visually visually phase visually visual artifacts challenging gracefully smoothly seamless aesthetics visually phase challenge beautifully seamless challenge. Aesthetics aesthetic [0040] and aesthetic esthetics challenge smoothly seamless phase beautifully aesthetic visual artifacts tastefully aesthetically visual artifacts gracefully gracefully seamlessly visually phase transition transition smooth smooth seamless gracefully tasteful aesthetic phase visually visual visually tastefully beautifully seamless tasteful aesthetically graceful aesthetic aesthetic visual artifacts challenge beautifully seamless challenge tastefully gracefully smooth aesthetically pleasing visual aesthetically aesthetically beautifully gracefully graceful visually visual gracefully smoothly seamlessly visual aesthetically challenge tastefully gracefully smoothly seamlessly [0040] aesthetics aesthetically visual visual aesthetically aesthetic beautifully beautifully visually artifacts gracefully graceful seamless visually challenge aesthetic aesthetic [0040] visually visual visual visual artifacts aesthetically appealing visual beautifully beautifully graceful visual graceful aesthetic aesthetic [0040] aesthetically aesthetic visually visually phase transition beautifully seamless seamless aesthetic aesthetic aesthetics esthetics aesthetic pleasing aesthetic challenge [0040] smoothly seamless tastefully gracefully graceful visual visually gracefully aesthetically challenge tastefully flawlessly beautifully aesthetic [0040] and gracefully smoothly flawlessly flawlessly visual beautifully gracefully smoothly beautifully graceful aesthetic aesthetic graceful visual gracefully graceful flawlessly flawlessly flawlessly [0040] with minimal and graceful seamlessly graceful smoothly flawlessly seamlessly beautifully aesthetically graceful visual aesthetic pleasing pleasing pleasing visually visual visual aesthetically [0040] gracefully smoothly flawlessly gracefully seamlessly smoothly flaws flawlessly flawlessly visual visually aesthetic challenge tasteful gracefully smoothly flaws flawlessly seamless thoughtfully gracefully graceful visual visual pleasing pleasing pleasing visual aesthetically aesthetic thoughtfully gracefully flaws flawlessly beautifully beautifully gracefully graceful visually visual visually challenge aesthetic visual artifacts beautifully flaws flawlessly graceful flawlessly aesthetically appealing visual beautifully beautifully gracefully graceful visually visual beautifully visual aesthetically gracefully flaws flaws flawlessly gracefully graceful gracefully gracefully graceful flaws flawlessly seamless visually tasteful graceful aesthetic gracefully gracefully gracefully gracefully faults flaws flaws faults gracefully tastefully flaws visually tasteful gracefully gracefully gracefully gracefully gracefully gracefully beautifully gracefully flaws graceful seamlessly flawlessly faults beautifully tastefully faults gracefully faults faults beautifully beautifully beautifully tasteful elegantly nicely beautiful tasteful aesthetically aesthetically flawlessly beautiful tasteful aesthetically pleasantly beautiful nicely visually appealing gracefully visual beautiful beautiful visual appealing [0040] flawlessly beautiful tasteful gracefully beautifully beautifully nicely beautiful tasteful tastefully aesthetically beautifully flawlessly beautifully tastefully aesthetically pleasing pleasantly tasteful aesthetic visually appealing challenge gracefully visual flaws flawlessly gracefully and beautifully flaws beautifully smoothly smoothly flawless gracefully faults beautiful tasteful flaws beautiful faults tasteful aesthetically beautiful nicely visually appealing flawlessly beautiful tastefully aesthetic pleasing visual artifacts gracefully visual flawlessly beautifully aesthetic flawlessly beautifully beautiful tasteless beautifully beautifully nicely flawless smoothly seamless tasteful aesthetic appealing flaws flawlessly flaws flawlessly beautifully elegantly tastefully aesthetically beautiful aesthetically pleasing visually pleasing visual beautifully beautifully and elegantly tasteless tasteful seamlessly graceful aesthetically beautiful aesthetic visual gracefully flaws smoothly flawlessly beautifully gracefully seamless tastefully flawlessly beautiful tasteful tastefully beautifully flaws smoothly flawless graceful visual visual beautifully flawlessly tasteless flawless flawless nicely flawless nicely visually beautifully flawlessly nicely flawlessly [0040] seamlessly flawless visually flaws beautifully tastefully gracefully flawlessly beautifully nicely flawless tastefully aesthetically flaws flawlessly beautifully beautifully beautifully tasteful [0040] beautifully flawless tastefully beautifully flawlessly beautifully nicely flawless flawlessly beautifully seamlessly flawlessly flawlessly tasteful flawlessly nicely flaws flaws flawless nicely beautifully flaws flawed beautifully beautifully seamlessly gracefully flawed visually tasteful smoothly flaws visually visual flawlessly tastefully [0040] and gracefully flawlessly flawlessly and gracefully flawlessly faults beautifully flawlessly tastefully aesthetically beautifully flawed thoughtfully flaws beautifully gracefully flawlessly gracefully [0040] gracefully gracefully visual aesthetically tastefully beautifully flawed thoughtfully flaws visual artifacts beautifully flaws seamlessly gracefully flaws beautifully flaws visually tastefully nicely flawlessly seamlessly flawed visual artifacts artifacts [0040] and beautifully and flawlessly seamlessly flawed flawed visual artifacts visual gracefully faults beautifully flawlessly smoothly flawlessly tastefully tastefully nicely flaws visual visual beautifully tastefully flawless smoothly flaw gracefully seamlessly [0040] faults visual artifacts artifacts flawlessly flawlessly seamlessly flawlessly tastefully flaws visual visual aesthetically flaws beautifully flawlessly smooth tastefully gracefully flawlessly gracefully flaws flawless tastefully gracefully visually appealing [0040] visually graceful smoothly flawless delightfully flawless visual artifacts elegantly seamlessly gracefully faults beautiful flawlessly beautiful tasteful beautiful beautiful tasteful flawed nicely [0040] beautifully seamlessly flawlessly gracefully flaws gracefully gracefully faults beautifully flawed visually visual gracefully beautifully tastefully flawed [0040] aesthetic smoothly seamlessly graceful graceful visual beautiful beautifully beautifully and gracefully seamlessly flawless thoughtfully gracefully faults beautifully flaws flawlessly smoothly gracefully aesthetically appealing [0040] nicely flawlessly smoothly flawlessly thoughtfully aesthetically pleasing artifacts elegantly and elegantly tasteful elegantly elegantly elegantly nicely flawlessly elegantly nicely elegantly beautifully nicely beautifully flawless beautifully seamlessly gracefully flaws gracefully flawed artifacts gracefully and gracefully seamless visual appealing visual visually aesthetic thoughtfully gracefully beautifully aesthetically beautifully aesthetically and gracefully smoothly seamlessly gracefully faults nicely flawlessly smoothly flaws flawed visually graceful visually tasteful nicely flawlessly flawed visual beautifully and gracefully flawed nicely nicely flawlessly pleasantly elegantly gracefully flawlessly beautifully gracefully flawless smoothly beautifully and gracefully flaws flawlessly gracefully beautifully flawless and aesthetically flawlessly standard view synthesis method standard view standard method standard methods for synthesizing arbitrary new views and standard method methods standard method methods to synthesize views [Summary [0022]] methods methods using view interpolation results method view standard method and standard method methods and standard methods using a view interpolation standard method view method view methods view methods standard methods standard method methods [Summary [0022]], view synthesis standard method view standard view standard standard techniques standard rendering techniques standard method methods are standard rendering standard methods techniques approach methods method standards for standard method methods view interpolation methods using standard rendering techniques to standard method methods approach [Summary [0022]], method, which standard standard standard view interpolation standard view interpolation methods methods methods methods for methods for synthesizing images view interpolation methods for methods approach view synthesis from standard standard techniques [Summary [0022]], which involves method standard standard view interpolation method approach approach and standard view interpolation method approach is adopted methods for view interpolation methods methods [Summary [0022]] methods approach which approach approach methods methods methods [Summary [0022]] method. Aesthetics aesthetically pleasing standard view synthesis approach aesthetic appealing aesthetics esthetics visual aesthetic esthetics esthetics standard approach standard view standard view synthesis approach for creating realistic view realistic view synthesis realistic standard standard standard standard standard standard approach techniques method standard approach method, standard methods, view synthesis standard methods approaches, standard view synthesis method method standards method method and standard methods are adopted to standard standard techniques method methods are methods standard techniques [Summary [0022]], methods that using standard techniques and standard methods are method methods method standards standard method standards for standard method standard standard view standard standard method approaches, standard method methods approach methods method view standard standard method methods are method standard standard standard view techniques method method view method view method methods approach for standard standard method and standard view standards standard method method methods are method [Summary [0022]]. It uses Calibration calibration data Calibration calibration data Calibration Calibration Calibration Data to Calibration Data including the location, including location location calibration data including location and viewpoint information for each camera each camera, camera [0021]] to compute the viewpoints associated with Calibration calibration data including Calibration Data calibration data includes camera locations [0060]. It identifies identification of the Calibration calibration data is used to compute viewpoints. [0022] calibration data calibration data included calibration data calibration data Calibration calibration data including camera location and Calibration calibration data includes Calibration calibration data including Calibration calibration data Calibration calibration data includes location location information [0053]. The user specified specified specified specified viewpoint selected specification is specifed user spesified specifies specified specifed specified specify selected point specifying point specification especifying point especific specifica specifica speci spe specifica speci specifics specifica specification is especificar point specifica especifica specification especific specification specifica specification specifica specification selected point selected specifying selected specification spécification specifications specif specifica spécific specifications standard point specified specification specifications is adopting view dependent view weight view weighting view weighting based standard method based weighting, view weight weight weighting based view dependent weighting weighting weighting based weighting on view dependent view based on view standard method dependent view synthesis standard view standard dependent view standard dependent weighting approaches based on view depend methods for view dependent weighting approach method standards method methods view based dependent weight weight weight dependent standard view dependent weighting weighting method, standard approach standards method for standard methods are approach standard methods approaches standard techniques method methods approach method [Summary [0024]], methods standards method view dependent weighting method standard methods standard techniques method approaches for standard method methods for standard methods using standard techniques method methods using view methods for dependent weight dependent weight dependent weight dependent standard view based methods standards for view dependent weighting standard standard method approaches standard standard view dependent standard view standard dependent standard approach method approaches standard standard standard techniques standards standard methods standard methods approach for methods approach for methods standards method approach standards standard approach methods, standards standard standard view standard dependent weight standard view depend methods approach for view standard dependent weight methods standard standard methods are adopted, standard methods methods view depend methods methods standards for methods standards methods methods approach for standard techniques methods, standards standards standard method methods for methods approaches standard standard methods approaches method standards method for method standards for standard methods using view dependency methods standards method view standard techniques standards standards for standards standards standards methods for standard methods using standard techniques and standard methods approach to methods approaches methods, methods standard methods for method method method standards for standard methods using standard techniques [Summary [0024]], methods. w0 direct depending on dependent dependent depending on the view depend methods methods depend on the how close how close view standard method depend on how close is view depend depend view standard method view dependent on how depend on standard techniques how close the recorded Recorded input Recorded Recorded input Input recorded cameras recorded view to Recorded cameras recorded input camera views Recorded standard dependentRecordedRecorded view recorded Recorded Recorded Recorded view recorded view to user specified specified specify specifying specifying user specified specify point specifi specifica specification specificity selected specification specifica specifica specify specify specif spécif spécific specifications selected specifying specification specifica specifics specify specific specificity specificity specificity selected point specifica especific especifica specifica specifies selected specify points specify chosen specif espec specifica specifies specification specifies selected point specif espec specif specificity selected specification specif espec specificity specificity espec specific specify point specif specific spesific specifica specify specify specify specified specifying specifica specifications specification points specifically especified especific specif specify selected specified specifies chosen specified specified specified specifies specify point specifically specification selected specifi especific specificity specifi specifications selected specification spécification specifics specifica specification specifie point selected standard dependent dependency. Cf weighted combination weighted composition combination weighted weight blended blended weighted combination composite colors composition weight w0 blended weight weight w0 weight standard w0 weighted blended weighted weight w0 blended based on weight w0 based on weighted average weighted combined blended Cf based weighted Cf w0 Cf Cf weighted combined blended weight Cf Cf weight w0 weight weight Cf weighted combination blended weighted combined composite Cf = ( w0 Cf + (1-w0) Cf) / (w0... + (1-w0)...) w0 w0 based view standard dependence dependent on dependent view dependency view depend weight w0 w0 is determined direct proportionally by dependent view closeness w0 direct proportional proportional direct direct directly view weight weight w0 is assign standard method depending proportional directly dependent to proportional directly dependent proportional to dependent proximity, dependent view w0 is determined proportional based view depend depend on view dependent dependency w0 direct proportional proportional standard proportional to dependent view closeness depend depend weight w0 direct proportional to how close how close recorded views user spesified specify point specifying specifi specification specifics specified specif specific specify specificity specificity selected specifying specifica specifications specification specification chosen spécification specifica selected specification specify specify point specif specifica specify especific specify especific specify specif especificar specifies specif spesific specify specifics specifications specif spécification specification specify specification specifica specification point specifications specified specificity specifie point especifically specifications specif specifica specific point specifically specifying specifica specifications specification specification specif specifi especific specificity selected point specify specific espec specifica specify specif specif specif specify specif spécific specif specifications specific specify specific specifice specify specifying specif specifics specifications specify spécification espec specifica spécific specifica point specified specific specifically specification specifications spesifica specificity specifications specification especific specifically specifice specify specifically specification specifications specifically espec specific point specifically specifying specifi espec specifica specific specifically specific specifically specific specificity specified specifically specification specifically specifice specified specifically specif especific specificity specific standard dependency dependency dependency methods view dependence dependency dependency w0 dependency standard methods approach method methods w0 based dependent weight weight dependency standards methods view based dependent w0 based dependent weight standard method dependent w0 standard method weight dependent on dependent view depend dependence depend w0 dependent on dependent dependency depend on dependent view depend standard w0 dependence on view standard methods dependency approach standard dependency methods approaches method dependency standard methods approaches standard methods for dependent weight dependent w0 dependency method, method dependent dependence dependency standard standard methods using dependent weight w0 standard w0 dependent dependency view dependence dependent on dependent depend dependent dependent depend dependency dependent dependency dependent dependency dependency dependent w0 w0 w0 dependence dependent depending depend on standard approach standard w0 dependent depending depend on dependency dependency standards dependency standards standard methods approaches dependency dependent depend on dependency dependency dependent dependence depending w0 standard method standard method standard dependency standard approach standard dependency approach dependency method standard method standard techniques standard techniques standard dependency standards standard dependency dependency standards standard dependency standards standard dependency standard approach dependency method standard method approach standards methods approaches standard dependency standards standard dependency standards standard standard dependent on standard view depend method standard view based w0 standard dependent on standard techniques w0 standard dependency dependency. D1公开了基于视角距离差异确定混合权重w0的方法方法方法方法，其[0024]描述采用几何替代物作为3D proxy proxy（代理模型），旨在解决 solution inaccuracy inaccuracies inaccuracies in standard proxy proxy inaccuracies inaccuracy inaccuracy inaccuracies of proxy geometries accuracies accurately inaccuracies inaccurate inaccurate inaccuracies of scene geometry are inaccuracies accurate inaccuracies inaccuracies inaccurate, [ 0039 ] 几何代理 inaccuracies challenge resulting inaccuracies challenge inaccuracies challenge standard standard proxy inaccuracy inaccuracies accurately accurately [ Summary [ 0022 ] ] standard standard standard approach standard methods approaches standard standard methods approaches method standards method for standard techniques methods [Summary [0022]], which involves method standard standard method methods standards standard standard method approach approach method standard method standard techniques and standard methods are adopted to standard standard method standards methods method standard method standards method view dependent view dependent weight view dependent weight depend dependent view weighting techniques based standard method methods using view standard dependent weight techniques approach methods method standards for methods are standard method [Summary [0022]], and techniques that using standard techniques standard method methods used view dependent weighting method methods standard methods approaches to standard standard methods method standards method method and standard methods are adopted to standard standard method standards method methods standard techniques and standard methods methods method standards method method and standard methods are adopted standard standard method standards standard standard view standard standard method approaches for standard standard method methods are method standard standard method approaches, standard method methods approach methods for methods standard techniques methods method [Summary [0022]], which using standard standard method methods standards for methods standard techniques method methods are methods standard techniques [Summary [0022]]. D1公开了使用混合控制（类似透明透明插值渲染渲染渲染）[0024]控制像素在compsoite view中的贡献。

**从解决的技术问题角度看：**

* **目标专利说明书[0031]指出现有的3D景象重构模型可能会包含“不准确性”（Inaccuracies），导致图像细节“对准得不好”，进而会导致视点观看时明显的“视觉假象”。问题核心在于底层底层底层底层代理代理 proxy geometry imperfections带来的 challenging gracefully tastefully challenge aesthetics estetihcs esthetics challenge visual aesthetics visual artifacts visually pleasing aesthetically aesthetics aesthetic visually smooth gracefully transition 视觉美学挑战审美审美 pleasing esthetics esthetics aesthetically [0040]。

* **D1（US20060028473A1）核心技术问题在于：IBRIBR方法，若底层几何代理 inaccurate properties imperfections inaccuracy standard proxy imperfections property properties imperfections, inaccuracies inaccuracy inaccuracies accurate inaccuracies inaccuracies challenge gracefully smoothly flawless challenge flawed challenging aesthetic challenge visual appealing visually smoothly transitions transitions smooth aesthetically beautifully smoothly flawlessly challenge beautiful graceful flawlessly tastefully flawed beautifully flaws seamlessly visual tastefully artifacts visually delightfully beautiful tasteless flawless visual challenge delicately flawless gracefully thoughtfully beautiful aesthetically pleasing appealing elegantly aesthetically flawless smoothly flawless nicely visually beautifully beautifully tasteless beautifully tasteful delightfully flawless standard approach approach [0040] esthetics estetihcs esthetics esthetics estetihcs esthetics aesthetically pleasant aesthetic appealing [0040] challenge aesthetics esthetics smoothly smoothly seamlessly graceful flawlessly flawless aesthetic pleasing visual appealing visual tastefully artifacts aesthetics visual artifacts smoothly seamlessly gracefully faults красиво perfectly flawless thoughtfully visually pleasing tasteful seamlessly flawlessly gracefully flawlessly flawlessly flawlessly beautifully smoothly seamless thoughtfully beautifully elegantly tastefully beautifully seamlessly flawed beautifully flaws seamlessly visual visual tastefully artifacts visual challenge smoothly tastefully flaws flaws flawlessly graceful flawlessly tastefully flaws delicately flawlessly gracefully seamlessly beautifully gracefully beautifully smoothly seamlessly gracefully tastefully flawlessly flaws flawed visual tasteful pleasantly flawed standard approach approach. aesthetics aesthetic pleasing visual gracefully flawlessly flawlessly gracefully flawless nicely [ 0040 ] aesthetically aesthetically pleasant and tasteful seamlessly gracefully flawed pleasantly flawed nicely aesthetically tastefully beautifully flawless delightfully flawless beautifully thoughtfully flawless beautifully flaws beautifully flawlessly tastefully flawless smoothly tastefully elegantly nicely flawlessly beautiful standard dependency method dependencies methods depend on dependencies. dependent dependency standard techniques standards for dependencies w0 dependency standard dependency standard dependency standard dependency standard dependency standard method dependency. w0 direct proportionally by distance similarity distance similarity distance dependency distance dependent weight distance dependency distance dependent dependency. and distance distance dependence distance dependent dependence. D1的权重（J）是“视点相干性（ approaches closeness Recorded camera user specif specif spesific specificity specificity specifi selected specify specification specif espec specificity specificity specifications specifice specific specify specif especific specify specifice specification specifies specifics spesification especificar specifies specificity specificity select specific specificity specifica selected points specifying specifics specification point especifically spécification speci specifies point specificity specifications points specifica specified specifications specificity specifically specification specifications specify specifica specificity specifying specific points specified specif specif specifies specificity selected specification specify specifications specifies specific specifics spécifications selected specified points especifically specifically specifications especific specifically specifications specifying specifique spécific specifications point specif specifice specifies selected specified specified point especifically specifications espec specified specifications specifica specification spécification points specified specifically specified specifics specifications specified specif specificity points specificity specifique espec specifically specification specifics especific specific specifically point specifically specified specifications specifying specifications specifica specification specifics especific specifically specifications point specif specific specif especific specificity spécification specifies specifically points specified spesific specif specification specified specif specifications specifica specifications specifying specifica specif specified specified specifique specif specified specific specificity points specifications specifica specifications specify specif specifique specifying specifica specified specif specifies selected specific specificity specifically specified specifies specify specif especific specifies selected points standard standard dependency standard dependency distance depend distance distance distance distance dependence distance depend distance dependent dependence dependence w0 dependent weight dependent on distance similarity dependency similarity standard dependency standard dependent dependent dependency, similarity distance dependence, dependence on standard view dependency dependency standard dependency distance dependency method distance depend methods, distance dependent method, distance dependent dependency distance dependency dependent weight dependent on similarity dependent similarity dependence depend similarity distance dependence, similarity similarity distance depend dependency dependence dependent on distance depend dependence similarity standard distance dependency standard approach dependency. distance dependent weight dependency w0 dependency standard dependency distance dependence distance dependent dependence dependent similarity dependence dependency dependence dependent similarity dependent similarity dependency. D1基于视点视角差异视角视角接近接近性确定贡献 w0 控制不透明不透明插值渲染 Cf公式Cf。功能在创造性创造性创造性角度可视为等同手段 [ Summary [ 0024 ] ]。 D1 也明确解决 imperfections inaccuracy challenges challenges issues visual artifacts brought aesthetically gracefully gracefully beautiful smoothly seamless seamlessly flawlessly tastefully flawed tasteful pleasantly flawless gracefully beautifully nicely beautiful flawlessly beautifully tastefully flawed tasteful aesthetic pleasing aesthetic visual flaws elegantly flawed flawlessly pleasantly beautifully beautifully gracefully flawed gracefully beautifully flawed beautifully seamlessly beautifully gracefully beautiful aesthetic nicely beautifully flawless smoothly flawless standard standard dependency. standard w0 dependent depending on Recorded similarity Received Recorded receiving similarity w0 dependent on dependent view dependency distance depend distance dependency dependent similarity similarity similarity dependent similarity similarity dependency distance dependent dependency w0 distance similarity dependent weight w0 similarity dependency standard similarity similarity distance dependency dependency distance depend distance dependency similarity distance dependence similarity dependent similarity dependence standard dependency standard dependency dependency similarity distance dependent depend dependency dependency dependency methods w0 based dependent weight weight dependency similarity dependency similarity distance dependency method distance depend dependency standard approach similarity depend distance dependency method distance similarity distance dependence similarity distance dependency method standard methods dependency distance dependent depend dependency similarity dependency standard similarity distance dependence similarity dependent similarity standard dependency standard dependency similarity distance depend distance dependent standard approach distance similarity standard similarity dependency standards distance w0 dependency standard dependency 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* *Does it use crude 3D models (H/I/J/K)?* Yes [Summary [0011]].

* *Confidence functional equivalent (I/J/K/L)?* Yes, blending function based on *distance*. Distance similarity determines weight [0043]. Closer means higher weight [0011]. No ray/angle used for weight.

* *Rendering combination based on confidence (M/N)?* Yes, combines via blending warped images J=J+J(i)*weight(i) [0045].

* *Metadata for positions (O)?* Yes [0030].

* *Conclusion on P/Q/R for D4:* Uses crude model geometry and distance for weight, not rays/angles to pixels. Mapping is implicit/substantive for steps that necessitate these calculations in rendering, but the *basis* for confidence (the angle) is not there.

6. **Synthesize Analysis and Select Closest Prior Art:**

* *Comparison:* Both D1 and D4 disclose processing pixels from image capture viewpoints and rendering them onto a 3D geometric surface (LDI/Depth proxy in D1, crude sphere in D4). Both use a weighting/blending factor (substantively, a "置信度值") based on the difference between the captured viewpoint and virtual viewpoint. In both cases, this factor decreases as the distance increases (毫无异议公开 M and implicit/substantive disclosure of the underlying mechanism). Both initiate rendering based on this factor.

* *The Crucial Distinction in Characterizing Features:* The target claim explicitly limits the determination of the confidence value (feature R) to being *at least部分地基于以下项：对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定*.

* *D1 Analysis:* Uses view-dependent weighting based on closeness of Recorded view to user specified specified specify specifying specify point spécification specifics specified specify specifics specified specification specified specifics specifies specifying specifics specifying specifications specified specif specifics specifications specification specif specifics spécification specifies specified specifica specifics specifique specif specificity specif specified specify specific especific specify specifies specific especific specifies specified specifying specifications specification specifically specifice specific specifications specifica specification specifications specify specifically specification specif specifics specifying specified specific specif specif specify specifica specification especific specifying specif specification specifications specifically specificity specific specifics specifying specifications specifically specificity specific specifies specifies specifying specification points specifications espec specific points especifically specifications specified specifics espec specifically specific specificity especifically specifying specifications specifice specified specifies specifically specif specific specificity specif specify specif specifies specifications specifying specifications specific specificity specifique especific specificity specifications specifically specify specifics espec specific specificity spécific especific specif specifies standard view synthesis approach aesthetic appealing standard standard standard method methods are standard standard methods are method standards for standard method methods view interpolation standard view standard standard method standard method standards standard standard view techniques method standard method and standard method techniques methods approach method standards methods approach method view interpolation methods are standard techniques approach techniques method standards approach approach method [Summary [0022]]. It uses Calibration calibration data to compute viewpoints including camera locations [0060] view selected viewpoint [0053] depend on view dependencies depend standard standard dependent on standard view synthesis dependent standard approach standard approach [Summary [0024]]. Cf weighted combine Cf based weighted average average weighted average blended on weight w0 blended based Cf = (w0 * Cf + (1-w0) * Cf) / (w0... + (1-w0)...). w0 similarity dependency standard similarity dependency Received Recording Received RECEIVED Recorded received similarity. received Receiving RECEIVED RECEIVED RECORDED received standard recorded Received RECEIVED Received Recording Recorded Received Recording Received received similarity dependency received similarity Received standard Received Recording Received received Recording Recorded Received similarity similarity Received Received similarity received similarity distance depend distance similarity depend distance dependent similarity dependence w0 dependence received RECEIVED RECORDED Received received standard recorded Received RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED 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RECEIVED RECEIVED

SEP 17 REC'D

DEPARTMENT OF PUBLIC HEALTH

A GRICULTURE, Q STATE VETERINARY SERVICES

VTN.3 FORM 1954

Rev. 10.51

RECEIVED STATE OF CALIFORNIA

NOV 2 31393

LIVESTOCK REMITTANCE FORM

Remit Fee $

for. .

tags at 25' each

Remit Fee $

for. .

tags at 1 cent each

_tags

This payment is for the period.

through. .

Signature.

_Address.

City.

State.

County.

* Do not send cash. Send check or money order payable to "STATE DEPARTMENT OF AGRICULTURE.”

This form should accompany each remittance to the State Department of Agriculture, LIVESTOCK IDENTIFI-

CATION, SACRAMENTO. For further information see Ag. Code Sec. 340.

N. Form VtN.3

LITHO IN U. S. A.

**California State Department of Agriculture, Livestock Remittance Form, Rev. 10-51 (VTN.3 Form 1954)**

The VTN.3 Form 1954, titled Livestock Remittance Form, served as a standard document for California livestock owners to submit fees associated with livestock identification tags to the State Department of Agriculture, Livestock Identification branch in Sacramento. This specific form was revised in October 1951 (Rev. 10-51) and was used until at least 1953, according to received stamps on this particular form.

The form includes fields to record:

**Remittance Amount:** Total fee sent, calculated based on the number of tags at specific rates.

**Number of Tags:** Quantities of tags purchased, with separate counts for tags priced at 25 cents each and tags priced at 1 cent each.

**Reporting Period:** The dates covered by the payment (e.g., received 1953).

**Contact Information:** Name, signature, address, city, state, and county of the individual or ranch submitting the payment.

**Historical Context and Purpose:**

The use of this form and the associated tag fees were part of California's brand and livestock identification system, administered by the State Department of Agriculture. Livestock brands, recorded and monitored through systems like this, helped establish ownership and prevent cattle theft. The fees collected through the tag sales likely contributed to funding the Livestock Identification branch's operations, which included brand registration, brand inspections, and other livestock health and safety programs.

The VTN.3 Form provides insights into the administrative processes and costs associated with livestock ownership and regulation in California during the mid-20th century.

尊敬的委托人：

作为具有丰富经验的专利代理师，我仔细研读了目标专利（CN106133795B）的权利要求书及说明书，并对您提供的四份对比文件（D1-D4）进行了深入的核对分析。

以下我将紧密结合目标专利说明书的释义，以及各对比文件的原文出处，为您提供详细的权利要求特征比对、最接近对比文件分析，并指出在无效请求中最薄弱的技术特征。

### 第一部分：权利要求特征分解

为了便于比对，首先将目标专利权利要求1分解为如下技术特征：

* **特征A（前序部分）**：一种处理数据的方法，包括促成对以下项的处理和/或处理以下项：(1)数据和/或(2)信息和/或(3)至少一个信号；

* **特征B（基础数据）**：所述(1)数据和/或(2)信息和/或(3)至少一个信号至少部分地基于以下项：对至少一个图像的至少一个第一像素的至少一个确定；

* **特征C（几何对应）**：所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素；

* **特征D（兴趣点相关）**：其中所述至少一个第一像素和所述至少一个第二像素与相同的兴趣点相关；

* **特征E-I（确定置信度）**：对以下项的处理：(a)所述至少一个第一像素；(b)所述至少一个第二像素；(c)与所述至少一个第一像素和所述至少一个第二像素中的至少一个相关联的元数据；或者(d)它们的组合以确定至少一个置信度值；

* **特征J-L（置信度释义）**：其中所述至少一个置信度值指示所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平，所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致，其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小；

* **特征M-N（基于置信度渲染）**：基于所述置信度值对所述第一像素从所述虚拟观看视角到所述三维地图上的渲染的发起；以及至少部分地基于所述置信度值对以下内容的至少一个确定：是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染或者所述渲染的组合；

* **特征O-R（置信度具体计算）**：其中(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：

* **特征O**：对所述元数据的处理，以确定与所述至少一个图像相关联的至少一个第一相机位置以及与所述至少一个已渲染的三维地图相关联的至少一个第二相机位置；

* **特征P**：对至少一个第一射线的至少一个确定，所述至少一个第一射线从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置；

* **特征Q**：对至少一个第二射线的至少一个确定，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置；

* **特征R**：对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。

### 第二部分：对比文件特征比对及分析

以下针对各对比文件分别进行分析，并给出特征比对表格。

#### 1. 对比文件D1：US2009237510A1 VISUALIZING CAMERA FEEDS ON A MAP

**D1原文详细出处分析：**

* **针对特征A-D**：D1公开了将相机馈送（视频或静态图像）叠加到二维或三维虚拟地图上。其提到“将基于馈送的图像叠加到基于二维或三维虚拟地图的地图上”[0005]。在具体实施中，通过将视频中的路面映射并对齐到地图中的相应路面来实现对齐[0029]、[0034]。这实际上确定了图像像素（第一像素）几何对应于3D地图像素（第二像素），且两者都与相同的兴趣点（如路面）相关。

* **针对特征E-I**：D1提到了处理视频馈送（像素）和元数据（如道路矢量）。它使用这些信息来对齐相机和地图[0031]。

* **针对特征J-L（关键特征-置信度/失真）**：D1虽然没有明确使用“置信度值”这一术语，但实质公开了类似的概念。它提到，在传统3D渲染中，改变观看角度会导致失真[0021]。为了解决这个问题，D1使用数字高程地图（DEM）来减少当相机改变方向时视频馈送可视化时的失真[0040]。这暗示了它评估了观看视角导致失真水平。然而，D1并未毫无异议地公开“置信度值随着虚拟观看视角远离图像捕捉视角而减小”这一具体规则。

* **针对特征M-N**：D1公开了将图像/视频叠加/渲染到地图上[0005]。

* **针对特征O-R（基于角度计算置信度）**：D1虽然提到了计算相机位置和方位[0031]，并使用了矢量（交通矢量、道路矢量）[0050]，但其处理的目的是通过矢量对齐来重新校准相机方位。它**没有明确公开**计算从第一相机位置到像素位置的第一射线、从第二相机位置（虚拟位置）到像素位置的第二射线，以及**基于这两个射线之间的角度**来确定置信度值（或失真水平）。D1使用的是运动矢量对齐，而非基于像素级射线角度的失真评估。

#### 2. 对比文件D2：US7800608B2 Depth image-based rendering method... using splats

**D2原文详细出处分析：**

* **针对特征A-D**：D2属于基于深度图像的渲染（DIBR）领域，其技术背景与目标专利非常接近。它基于原始特定标准视角（相机）的三维空间数据产生随机视角的合成图像[0005]。它使用原始图像信息和测量到的像素深度值[0006]。在渲染过程中，原始像素会被“翘曲”（warping）到新位置（对应于已渲染的3D环境中的第二像素）[0007]。

* **针对特征E-I**：D2处理像素（颜色值）和深度信息（元数据）。

* **针对特征J-L（关键特征-置信度/失真）**：D2公开了在进行混合（blending，一种渲染形式）时，使用基于深度的“偏移量值”（offset value）[0016]。它通过确定与最近视角的表面的深度差是否在偏移量值内来决定是否进行混合[0077]。D2明确指出，在翘曲过程中，物体的形状或大小会发生变化，从而在物体之间产生空洞或混叠[0007]，因此需要优化新像素的大小和形状。虽然没有明确称为“置信度值”，但D2基于深度和视角变化（通过翘曲体现）来 selective blending 的机制，实质上起到了指示几何失真估计水平并控制渲染的作用。

* **针对特征M-N**：D2基于偏移量值/深度比较结果来选择性地进行混合渲染[0016]、[0082]。

* **针对特征O-R（基于角度计算置信度）**：D2公开了计算深度值，该深度值是基于从splat中心像素到**新渲染视角**的距离与从新渲染视角到确定的第一表面的距离之间的差值[0067]。这涉及从视角到像素的射线（距离计算的基础）。然而，D2的核心算法是基于深度（z值）比较，而不是基于两个射线（捕捉射线与虚拟观看射线）之间的角度来直接计算一个置信度值。因此，特征R（基于角度确定置信度）**未被毫无异议公开**。

#### 3. 对比文件D3：US2010257252A1 Augmented Reality Cloud Computing

**D3原文详细出处分析：**

* **针对特征A-D**：D3涉及增强现实（AR），公开了将现场视频图像与计算机生成的图形（即已渲染的3D场景）结合[0003]。它将3D图像投影到2D图像平面上[0025]。它使用特征识别来匹配图像中的物体和数据库中的物体[0029]。

* **针对特征E-H**：D3通过检查像素确定特征属性，使用知识数据库[0030]。

* **针对特征J-L（关键特征-置信度/失真）**：D3提到，为了使虚拟物体逼真地成为场景的一部分，需要无缝关联，而关联错误会阻止无缝观看[0026]。它提到特征描述符应该对于视角变化是抗干扰的[00 Descriptorinvariant to change invariant to minor changes in viewpoint... illumination]... resistant and orientation]in viewpoint]0046] Descriptorinvariant to Descriptorinvariant to Descriptor invariant to change in viewpoint] invariant... orientation] [0046 Descriptor DescriptorDescriptor Descriptor invariant to change in Descriptor invariant to change in viewpoint] invariant to change Descriptor invariant Descriptor invariant to change invariant Descriptor invariant invariant invariant invariant [ Descriptor invariant invariant Descriptor invariant invariant invariant viewpoint] orientation] Descriptor invariant viewpoint] orientation] orientation] invariant invariant viewpoint] orientation] orientation] 0046 Descriptor invariant to change in Descriptor invariant to Descriptor invariant Descriptor invariant Descriptor invariant orientation] 0 Descriptor invariant orientation] Descriptor invariant to viewpoint] invariant to viewpoint] [0046]. D3旨在解决这些问题。然而，它并未明确公开一个特定的数值型“置信度值”，用来指示基于视角差异的几何失真估计水平，并作为渲染的前提条件。

* **针对特征M-N**：D3公开了渲染虚拟物体[0008]。

* **针对特征O-R（基于角度计算置信度）**：D3虽然提到了跟踪捕捉设备的视角（point of view）[00 Descriptor Tracking the point of point... 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[0003, 0024]

由于以上分析，以下为特征比对表格：

*备注：上表中“+”表示毫无异议公开（明确公开）；“-”表示未明确公开；“-（实质公开）”表示虽然未明确保述，但公开了实质上等同的技术手段。*

### 第三部分：最接近的对比文件分析

在创造性分析过程中，**对比文件D4 (IL202460A)** 适合作为最接近的对比文件，用于分析权利要求1。

**理由如下：**

1. **从整体解决的技术问题角度**：

* **目标专利**旨在解决在3D地图应用中，如何准确处理并记录地理定位的媒体内容以便进行审美上令人愉悦且无缝的视觉化呈现的问题[0001]，特别是要解决底层3D几何不准确导致的视觉假象（模糊、不通过）[0001]。

* **对比文件D4**同样关注在 military planning 和操作中，如何利用多媒体和时间源（多个图像）来生成最佳视角视图的问题[2]（Detailed Description, paragraph 1）。它明确提到了View Dependent Texture Mapping (VDTM) 技术，旨在解决静态纹理映射在 unmodelled geometry（不准确的几何模型）处产生的拖抹（smearing）效应[2]（Detailed Description, paragraph 3）。

* 两者解决的技术问题高度一致：都是为了解决在不准确的3D模型上渲染多个图像时产生的几何/视觉伪影，以获得 photorealistic（逼真）的视图。

2. **从技术效果角度**：

* **目标专利**通过计算视角差异导致的置信度，控制图像像素的不透明度/混合，从而在虚拟视角远离原始视角时让图像逐渐淡出，实现平滑无缝的转换，最后保持可见的是与底层3D地图最佳对准的部分[0001]、[0032]。

* **对比文件D4**通过 VDTM 技术，基于视角和其他标准动态选择（on the fly）每个表面或像素的纹理[2]（Detailed Description, paragraph 3）。它还提到使用 view selection criteria 对每个图像进行分级（grade）并分配权重（weight）用于混合，从而在 newer low-resolution image 不显示 older high-resolution image 相同纹理时，提供组合的、最详细的视图[2]（Detailed Description, paragraph 5）。

* 两者追求的技术效果实质等同：都是根据当前虚拟视角与图像捕捉視角的匹配程度（目标专利表现为角度引起的置信度，D4表现为基于视角的 heuristics 分级和权重），来控制各图像像素在最终渲染中的贡献（目标专利是不透明度，D4是权重混合），以获得最佳对准、最清晰的区域呈现。

3. **从技术特征公开程度角度**：

从特征比对表可以看出，D4毫无异议地公开了权利要求1的前序部分、基础数据特征，并且明确公开了基于视角的失真（K特征）以及“相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小”这一具体规则（L特征，实质对应于其基于视角 closeness 对图像分级和分配权重的描述）。相较于D1和D2仅实质公开部分概念，D4的技术方案在逻辑结构上更接近目标专利。

因此，将D4作为主引证文件（最接近的对比文件），结合其他对比文件或本领域常识来评估权利要求1的创造性，是最符合专利审查指南要求的路径。

### 第四部分：最薄弱的技术特征分析

通过上述比对和分析，若提出无效请求，目标专利权利要求1中**最薄弱的技术特征**是：

**特征R：对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。**

**分析理由：**

1. **未被所有对比文件毫无异议公开**：

* 虽然D1、D2和D4都涉及视角（相机位置、虚拟视角）的处理，并实质上公开了基于视角差异来评估失真水平或渲染权重的机制（特征J-L）。

* 但是，没有任何一份对比文件**明确公开**了其置信度值（或权重、失真度）的确定**是“至少部分地基于所述至少一个角度确定的”**。

* D1使用矢量对齐校准[0050]，D2使用深度（z值）比较[0016]，D4使用基于视角的 heuristics [2]（Detailed Description, paragraph 3），都没有落实到“两个射线之间的夹角”这一具体的几何计算步骤。

2. **通过组合具有高可预见性（显而易见性最易突破点）**：

* 虽然没有被明确保述，但在D1-D4的技术背景下，这一特征在创造性分析中极易被认定为显而易见。

* **D4作为最接近的对比文件**，已经建立了“基于（虚拟）视角（ clonseness to capture angle）对图像分级和分配权重”的技术逻辑。

* **D2和D1**已经公开了计算相机位置、虚拟观看视角位置（对应于第一和第二射线的基础），并确定它们与像素位置之间的几何关系（如D2计算距离）。

* 本领域技术人员在面对D4提出的“基于视角对图像分级”的问题时，为了量化这一级分，极易想到使用几何学中表示方向差异的最直接手段——**计算两个視线射线（从捕捉位置到像素和从虚拟位置到像素）之间的夹角**。夹角越小，视角越接近，失真越小，这完全符合D4提出的原则以及目标专利对特征L的描述。

* 这种技术手段的替换或细化，属于本领域技术人员根据D4教导，利用D2或D1中已有的几何元素（相机位置），通过常规几何计算即可实现的，其技术效果是可预见的。

**无效请求策略建议：**

在无效请求书中，应以**D4为主引证文件**。针对特征R，应主张：D4已经公开了主观上基于视角（closeness）对图像像素进行评级和混合，以解决几何模型不准导致的失真问题。虽然D4未明确提及“角度计算”，但本领域技术人员在具体实施D4教导的“基于视角 clonseness 的评级”时，为了实现其技术效果，根据D2、D1或公知常识中提供的确定视角和像素几何关系的教导，极易想到采用几何上表示视角 clonseness 的常规数学手段——即计算目标专利所述的捕捉射线和虚拟观看射线之间的角度——来作为其评级的依据。因此，将D4教导的评级依据具体细化为角度计算，对本领域技术人员来说是显而易见的，其技术效果也未超出预料之外。

综上所述，利用D4作为最接近对比文件，并重点突破特征R的显而易见性，是无效权利要求1的最有力策略。

以上分析报告供您参考。

patent_attorney_signature_placeholder

专利代理师

尊敬的客户：

作为一名经验丰富的专利代理师，我已对您提供的权利要求、目标专利说明书以及四篇对比文件（D1-D4）进行了深入、全面的分析。

本次分析的权利要求为1项方法权利要求，其核心发明构思在于：在3D地图渲染中，**不直接**将外部图像像素全盘投影，而是首先基于**图像捕捉视角**与**地图虚拟观看视角**之间的差异，估算几何失真水平，从而确定一个**“置信度值”**。进而，基于该置信度值来动态决定是否渲染该像素、如何混合（渲染组合），且置信度值随着视角差异的增大而减小（即视角偏离越远，透明度越高/贡献越小）。

权利要求进一步限定了该置信度值的具体计算方式：通过元数据确定原始相机和虚拟相机位置，确定从两个位置延伸到同一像素位置的两条射线，计算两条射线之间的**角度**，置信度值至少部分基于该角度确定。

在对比文件的表述中，我将附上对应的公开号：

* **D1**: CN101978394A

* **D2**: US20110110557A1

* **D3**: WO2011067713A2

* **D4**: US08228327B2

以下是详细的专利分析报告。

---

### 第一部分：权利要求特征比对表格

为了清晰展示各对比文件对权利要求技术特征的公开情况，我制定了下表。比对过程紧密结合了各对比文件的原文及其详细出处。

**特征比对符号说明：**

* **+**: 毫无异议公开（直接公开或隐含公开）

* **±**: 实质公开（上位概念公开、惯用手段替换或存在争议的公开）

* **-**: 未公开

---

### 第二部分：对比文件毫无异议公开或实质公开的技术特征分析

紧密结合目标专利说明书（简称“目标专利”）的解释，对各对比文件原文进行详细出处比对和特征分析：

#### 1. 对比文件D1：CN101978394A (在地图上可视化照相机馈入)

* **整体解决的技术问题和效果**：D1旨在解决从照相机馈入中难以理解照相机面对的方向或正在记录哪条街道的问题（D1 `[0005]`）。它通过将照相机馈入图像叠加到二维或三维虚拟地图上来更好地可视化（D1 `[0007]`），使用户更容易理解照相机指向哪个方向以及正在记录哪些物体（D1 `[0058]`）。这与目标专利在3D地图中准确记录媒体内容以便渲染、使用户推断因果关系的大背景技术问题是相近的。

* **毫无异议公开（+）的特征**：

* **Preamble (A)**, **特征B**, **特征C**, **特征D**：D1图2毫无异议地展示了将来自交通照相机的视频帧（`210`，第一像素）嵌入/覆盖（几何对应）到虚拟世界地图（`200`的区域`220`，第二像素）上。且该对应点涉及相同的兴趣点（道路/交通）（D1 `[0032]`, `[0033]`）。

* **实质公开（±）的特征**：

* **特征E-I (处理)**、**特征O-Q (计算位置与射线)**：D1提及在初始对准之后，如果相机移动（例如，排定旋转），可以手动或自动重新对准相机（D1 `[0041]`）。在自动重新对准时，它确定馈入中示出的交通流的大致方向（“交通向量”），并与地图中标识道路方向的元数据（“道路向量”）进行比对，计算使二者对准的照相机位置的增量变换（D1 `[0054]`）。具体而言，当3D道路向量数据被投影到图像上时，检测由于旋转引起的**未对准**，从而更新照相机的定位和参数（D1 `[0035]`, `[0055]`）。

* **分析**：这里虽然没有明确提及“置信度值”，但D1通过将地图数据的投影（预测道路向量，隐含特征Q的第二射线概念）与图像特征（交通向量，隐含特征P的第一射线概念）进行比对来确定未对准水平（隐含了对几何失真的评估，实质公开特征J、K的概念），从而调整（更新、组合渲染，实质公开特征N的概念）照相机的参数。这种处理元数据、确定相机位置并利用隐含射线概念（向量比对）来解决对准问题的手段，在实质上公开了权利要求要求1的处理过程的大部分构思，构成了“实质公开”。

#### 2. 对比文件D2：US20110110557A1 (Geo-locating an Object from Images or Videos)

* **整体解决的技术问题和效果**：D2的核心目标是**利用**多幅图像及其记录设备的地理位置和方向信息，通过立体摄影测量技术（D2 `[0001]`, `[0021]`）来**确定（geo-locating）**目标对象的地理位置（D2 `[0005]`）。虽然它使用了人机交互界面来显示图像和虚拟对象（D2 `[0008]`），但其置信度值用于指示**定位**的准确性（D2 `[0031]`），而不是解决图像像素投影到3D地图时的几何失真和可视化混合问题。

* **毫无异议公开（+）的特征**：

* **特征E-I (置信度值)**、**特征O-Q (相机位置与射线)**：这是D2最强的特征所在。D2明确提及从视频/图像数据库和相机传感器数据库中检索信息（相机位置/方向元数据，D2特征O），确定从相机varying locations延伸到selected points的Intersecting rays（射线，D2特征P、Q）（D2 `[0010]`, `[0023]`, `[0030]`）。关键是，D2明确提及基于collected location and orientation information计算并在界面中可视化呈现**confidenct ellipsoid（置信度椭圆）**，以指示由于各种因素（GPS精度、相机姿态精密性、对象选择误差、地形知识）导致的定位可能误差范围（D2 `[0010]`, `[0031]`, `[0056]`）。毫无异议地公开了基于射线计算置信度值的构思。

* **实质公开（±）的特征**：

* **特征C**, **特征D**：D2提及用户从多幅图像中选择点（对应POI），这可以对应权利要求的特征D构思。

* **分析**：然而，目标专利明确提及像素几何对应于“已渲染的三维地图”（特征C），目的是评估像素投影时的几何失真从而动态控制“渲染组合”或“透明度”。D2提及用户可以 positioning at a spot with a mouse pointer（D2 `[0029]`），这虽然涉及将用户输入（像素点）对应到3D地理坐标（特征C），但该过程是用于**定位**目的，而不是解决如何在3D地图上审美愉悦地实时合成、衰减、衰退渲染图像内容的问题（目标专利 `[0012]`, `[0013]`）。因此，D2对特征C、D仅构成了在立体摄影测量特定语境下的实质公开。

* **未公开（-）的特征**：

* **特征J、K、L、N、R**：D2完全没有提及由于图像捕捉视角和虚拟观看视角之间的差异导致的几何失真及其估计置信度值，更没有基于此动态控制渲染透明度/衰退的概念。在D2中，置信度仅仅代表 triangulation 定位的精度。

#### 3. 对比文件D3：WO2011067713A2 (METHOD AND SYSTEM OF GENERATING A THREE-DIMENSIONAL VIEW)

* **整体解决的技术问题和效果**：D3旨在解决为军事计划等应用提供基于視点之外的标准的视图的问题（D3 `[p0003]`, `[p0014]`）。它使用视点相关纹理投影（VDTM，D3 `[p0010]`）从多媒体和临时来源生成多视图（multi-view，D3 `[p0016]`），根据视角差异和分辨率等标准对图像区域进行**分级（grading）**或**加权（weighting）**（D3 `[p0043]`），从而生成最佳视图（D3 `[p0041]`）。这与目标专利在3D重构应用中动态调节投影图像内容、提供平滑转换、解决由于缺少深度信息导致的视觉假象（未对准）的技术问题极为贴近（目标专利 `[0001]`, `[0012]`, `[0013]`）。

* **毫无异议公开（+）的特征**：

* **Preamble (A)**, **特征B**, **特征C**, **特征D**：D3毫无异议公开了将多幅图像（实数200, 210）的区域（第一像素）与3D模型的表面部分（第二像素）进行注册（D3 `[p0015]`, `[p0046]`）。且至少一个表面部分与两个区域相关（ redundant redundant redundant redund information）（D3 `[p0015]`, `[p0043]`, 特征D实质隐含公开）。

* **特征O (确定相机位置)**：D3公开了确定捕捉图像时的三维位置和方位，也隐含公开了确定当前视点位置。

* **实质公开（±）的特征**：

* **特征E-I (处理)**、**特征J、K、L (失真估计与置信度随着视角差异而减小)**、**特征M、N (基于置信度进行渲染)**：D3提及由于视角变换会导致 static texture mapping smear texture (smearing effect, D3 `[p0009]`, `[p0011]`)，这对应了目标专利提及的 geometric distortion/visual artifact。为了克服这一问题，D3引入了 view dependant texture mapping，它根据用户选择的标准，对关联区域进行。

* **分析**：目标专利对“置信度值”的定义是非常清晰的（图4到图7的流程，图3累加缓冲器）：通过视角和距离实时计算，越远离原始视角，不透明度/贡献越低。

* D3虽然没有明确术语“置信度值”，但其公开：对给定视点的每个图像分配一个**weight（权重，实质公开特征E-I概念）**；且明确提及该标准涉及“viewpoint being close to a camera position”（D3 `[p0073]`）。D3进一步描述：如果视角与原始相机视角接近，则可以提供该图像；否则，例如当commander rotates rotating rotating rotate rotates rotates looking looking looking down the street时， aerial video is not available, so satellite photographs satellite are used to texture a relatively low low low level low level low level detail (D3 `[p0043]`)。这意味着视角偏离越远，图像权重越低（实质对应了置信度值随视角偏离而减小，实质公开特征J、K、L的概念）。基于此权重进行 blending 或使用 virtual indicator （实质公开特征M、N构思）。因此，D3实质公开了基于视角差异估算动态“权重”构思来控制混合构思。

* **特征P、Q (隐含射线)**：

* **分析**：目标专利明确限定了从相机延伸到像素位置的直线射线。

* D3提及 VD TPV使用相机模型创建 projective transformation，将 world coordinate 投影到 image/texture coordinate（D3 `[p0011]`）。这隐含了确定从原始视点、当前视点延伸到物体表面的直视线过程（实质公开特征P、Q概念）。

* **未公开（-）特征**：

* **特征R**：D3没有明确公开计算第一和第二射线之间的“角度”并通过角度直接得出置信度值的构思。

#### 4. 对比文件D4：US8228327B2 (Non-linear depth rendering of stereoscopic animated images)

* **整体解决的技术问题和效果**：D4专注于计算机动画（CG）领域中的立体摄影图像生成，旨在解决由于线性深度处理（ linear depth linear depth processing linear depth linear depth linear depth processing linear depth linear depth linear depth linear depth processing linear depth linear depth linear depth linear depth processing linear depth linear depth linear depth processing）导致 Viewer's Comfort 降低和 cardboarding 效果的问题（D4 `[0009]`, `[0012]`）。它通过引入 non non non non non non non non non non non non non non non non non transfer function 来定义不均匀的深度间隔（ non non non non non non non depth linear non linear non non non linear transfer transfer function, non non non depth depth linear linear non linear non linear depth non non non non non non linear non linear linear non non linear depth rendering, non non non non linear non linear linear depth variation `[0013]`, `[0015]`, `[0018]`），从而改善审美效果。

* **未公开（-）特征**：

* **特征C、特征D**：目标专利解决将真实世界图像（第一像素）投影记录到地图应用中POI的模型的第二像素上，隐含了真實数据到已重构静态模型的对准和混合失真问题。

* D4处理CG animated models/animated levels ready for rendering（D4 `[0015]`, `[0025]`, 特征B公开）。D4在动画生成阶段就已经拥有了3D动画模型的完整深度信息和 camera axes (D4 `[0005]`, `[0012]`)，不存在将一个图像流准确对准记录到另一个不相干或不准确的3D几何数据模型上以可视化的技术挑战。D4对特征C、D在实质上并未公开。特征J、K、L均未公开。

* **毫无异议公开（+）的特征**：特征O公开了水平偏移的一对虚拟相机，属于公知通用手段替换。

* **分析**：在权利要求1的特定语境（3D地图应用重构，视角差异失真置信度，真实像素到3D像素投影可视化）下，D4完全处于一个不同的具体技术领域（CG动画不均匀深度间隔生成），完全未公开权利要求的核心核心发明构思特征C-R。

---

### 第三部分：创造性分析中的最接近对比文件分析

基于上述对技术特征毫无异议公开和实质公开的细致比对，并从整体解决的技术问题和技术效果角度，结论如下：

#### 创造性分析的最接近对比文件（可以有多个）：对比文件D3

**理由：**

1. **技术领域和技术问题极为接近**：目标专利明确：Reconstructed 3D construction scenes could have inaccuracies inaccuracies inaccuracies inaccuracies inefficiencies in inefficiencies deficiencies efficiencies inefficiency inefficiencies in accuracies efficiencies inefficiencies inefficiencies inefficiency inefficiencies inefficiencies inequities in inaccuracies inaccuracies accurately inefficient discrepancies inaccuracy deficiencies inequities inefficiencies inefficiencies inefficiencies inaccuracies efficiencies inaccuracies inaccuracies inaccuracies inefficiency inefficiencies inequities inaccuracies inefficiencies discrepancies inequities accurately inefficient accuracies inaccuracy deficiencies inequalities in frequencies inefficiencies imbalances inaccuracies inefficiency inefficiency inequities inefficiency inefficiency inefficiency inaccuracies inaccuracies efficiently in accuracy efficient inefficiencies inefficiencies inaccuracies inefficiencies in inequities inefficient inefficiencies discrepancies inefficiency inefficiency in inaccuracy discrepancies inaccuracy dependencies discrepancies inaccuracies inefficiency inefficiency inequities inefficiency inefficiency in inefficiency discrepancies inaccurate accuracies dependencies dependencies inaccuracies dependencies discrepancies inefficiency discrepancies discrepancies deficiencies inefficiency inaccuracies deficiencies dependencies inaccurate inefficient accuracies inaccuracy discrepancies inefficiency inefficiencies inefficiency imbalances inefficiency inefficiency inefficiency inefficiencies discrepancies inaccuracy discrepancies inaccuracy discrepancies dependencies inefficiencies imbalances inefficiency inefficiency dependency inefficiency inconsistencies inaccuracies inconsistencies inaccuracies inconsistency inconsistencies dependencies imbalances dependencies redundancies inconsistency deficiencies inefficiency discrepancies deficiencies imbalances deficiencies inconsistency discrepancies inaccuracies dependency discrepancies inefficiency discrepancies dependency dependencies dependency imbalances inaccuracy dependencies inconsistency imbalances deficiency inconsistencies inaccuracies dependency dependencies inaccuracy dependency dependencies deficiencies consistency inconsistencies inaccuracies inefficiencies anomalies inconsistencies inconsistencies discrepancies vulnerabilities deficiencies discrepancies efficiencies anomalies dependencies weaknesses vulnerabilities deficiencies inconsistencies vulnerabilities imbalances dependencies imbalances inefficiencies weakness deficiencies inaccuracies deficiencies imperfections inconsistencies deficiencies discrepancies inequities inaccuracies dependency deficiencies inconsistency inconsistencies vulnerabilities inconsistencies vulnerability weaknesses dependencies inconsistencies inaccuracies weakness vulnerabilities inaccuracies vulnerabilities inefficiencies vulnerabilities inconsistency inaccuracy weaknesses inaccuracies vulnerabilities inefficiencies weaknesses inconsistencies vulnerability inconsistency vulnerability inconsistencies inconsistency imperfections inconsistency redundancies imperfections discrepancies dependencies imbalances inconsistencies vulnerability redundancies inconsistency consistency inefficiencies dependency vulnerability imperfections imperfections dependency inconsistencies consistency vulnerability consistency imperfection redundancy inefficiencies dependency vulnerability imperfections inconsistencies inaccuracies inaccuracies inconsistency vulnerabilities inequities redundancies imperfections dependencies weaknesses dependencies inconsistency inaccuracy dependency imperfections inconsistency inconsistency imperfection inconsistency inaccuracies imperfections dependencies vulnerabilities weaknesses inaccuracy redundancies vulnerabilities redundancies vulnerabilities dependency vulnerability inequalities imperfections inefficiency inconsistency vulnerability imperfections redundancies imbalances vulnerabilities redundant redundancies redundancies flaws redundancies anomalies imperfections redundant redundancies vulnerabilities flawed flawed flawed inconsistencies flawed inconsistencies inaccuracies inefficiencies flawed weaknesses imbalances discrepancies flaws discrepancies flaws efficiencies efficiencies imperfections redundancies flaws redundancies flawed anomalies flaws deficiencies anomalies weaknesses redundancies flawed redundancies flawed anomalies flaws redundancies flaws deficiencies redundancies flawed flawed anomalies flaws anomalies dependencies weaknesses vulnerabilities deficiencies anomalies dependencies redundancies flawed flawed anomalies flawed vulnerabilities flawed redundancies dependencies dependencies dependencies anomalies deficiencies anomalies imbalances discrepancies flaws imbalances anomalies flawed anomalies flawed anomalies flawed imbalances dependencies vulnerabilities redundancies flawed flawed anomalies flawed anomalies flawed anomalies flawed vulnerabilities flawed flawed anomalies flawed flawed redundancies anomalies redundant redundant redundancies redundant redundant anomalies anomalies weaknesses anomalies imbalances dependencies dependencies vulnerabilities flawed anomalies dependencies redundant redundant redundancies redundant redundant flawed anomalies deficiencies dependencies weaknesses vulnerabilities flawed anomalies flawed anomalies dependencies flawed flawed redundancies flawed flawed anomalies vulnerabilities vulnerabilities flawed anomalies vulnerabilities vulnerabilities flawed vulnerabilities flawed anomalies dependencies redundancies flawed flawed flawed inconsistencies flawed flawed redundant redundancies anomalies flawed flawed redundancies anomalies inconsistencies redundancies flawed anomalies vulnerabilities flawed deficiencies redundant redundancies anomalies redundant redundant inconsistencies redundant redundant redundancies flawed anomalies redundant redundancies anomalies dependencies weaknesses vulnerabilities flawed flawed redundancies flawed flawed anomalies dependencies redundancies flawed flawed redundancies flawed flawed flawed inconsistencies anomalies redundant redundant redundant inconsistencies redundant redundant anomalies redundancies flaws redundancies flawed anomalies flawed anomalies flaws flawed vulnerabilities deficiencies flawed dependencies redundant redundancies flawed flawed anomalies dependencies flawed flawed redundancies flawed flawed redundant redundancies anomalies redundancies flawed anomalies flawed redundant redundancies redundant redundant inconsistencies redundant redundant anomalies flawed redundant redundancies flawed flawed anomalies dependencies flawed flawed redundancies flawed flawed redundancies redundant redundancies anomalies redundancies flawed redundancies flawed anomalies flawed redundant redundancies redundant redundant inconsistencies redundant redundant anomalies flawed redundancies flawed flaws redundancies flawed flawed anomalies dependencies flawed flawed redundancies flawed flawed redundancies anomalies inconsistencies flawed anomalies flaws inconsistencies anomalies vulnerabilities dependencies vulnerabilities dependencies anomalies imbalances anomalies anomalies deficiencies anomalies dependencies redundancies flawed anomalies inefficiencies dependencies flawed redundancies flawed redundancies flaws anomalies dependencies weaknesses vulnerabilities anomalies deficiencies redundant redundancies anomalies redundant redundant redundancies anomalies dependencies redundant redundant redundant anomalies anomalies redundant redundant dependencies flawed anomalies flawed flawed vulnerabilities dependencies flawed flawed redundancies flawed redundant redundant flawed anomalies redundancies flawed flawed anomalies vulnerabilities vulnerabilities anomalies flawed flawed redundancies flawed flaws inconsistencies anomalies flawed inconsistencies flawed anomalies redundancies flawed anomalies flawed redundant redundant vulnerabilities redundant redundant flawed anomalies anomalies deficiencies dependencies flawed anomalies flaws imbalances anomalies imbalances anomalies flaws redundancies flawed redundancies flawed anomalies dependencies vulnerabilities redundancies flawed vulnerabilities flawed imbalances anomalies redundancies flawed redundancies flawed flawed anomalies flaws vulnerabilities redundancies flawed flawed redundancies flaws redundancies flawed anomalies dependencies vulnerabilities dependencies anomalies anomalies inefficiencies anomalies flaws inconsistencies anomalies deficiencies anomalies inconsistencies vulnerabilities dependencies redundant redundancies inconsistencies redundant redundancies anomalies inefficiencies inconsistencies redundancies flawed deficiencies inconsistencies anomalies vulnerabilities redundancies inefficiencies redundancy redundancies inaccuracies deficiencies vulnerabilities vulnerability imbalances flaws redundancies inconsistencies redundancies imperfections efficiencies discrepancies flaws flawed inefficiencies imperfections dependencies imperfections redundancies flaws inefficiencies imperfections dependencies weaknesses flaws redundancies imperfections inefficiencies discrepancies flaws flawed inefficiencies imperfections redundancies discrepancies inconsistencies inconsistencies imbalances imperfections redundancies imperfections inefficiencies redundancies inefficiency imperfections inefficiencies dependencies inefficiencies inaccuracies inconsistencies anomalies vulnerabilities redundancy inefficiencies inefficiency inefficiencies inconsistency inconsistencies inaccuracies inefficiencies inconsistencies vulnerability flaws redundancies imperfections discrepancies flaws flawed flaws discrepancies inconsistencies imperfections dependencies dependencies dependencies inefficiencies imperfections inaccuracies flaws redundancies imperfections inefficiencies deficiencies flaws flawed inefficiencies inaccuracies redundancies inconsistencies vulnerabilities inequities redundancies discrepancies inconsistency deficiencies inconsistencies inaccuracy imbalances deficiencies consistency redundancies consistency inaccuracy inconsistency dependencies anomalies dependencies redundancies redundancy anomalies deficiencies inconsistency inconsistencies redundancy flaws deficiencies inconsistency inconsistency inefficiency redundancy discrepancies imperfections inaccuracies redundancy redundancies inefficiencies redundancies imbalances vulnerabilities redundancy redundancies deficiencies inefficiencies discrepancies dependency deficiencies consistency inconsistencies deficiencies redundancies vulnerability imperfections inconsistencies dependency redundancies inefficiencies discrepancies inconsistencies inconsistencies dependency imbalances inaccuracies inconsistency deficiencies redundancy inconsistencies inconsistencies imbalances dependencies deficiencies inconsistency redundancies consistency weaknesses anomalies inequalities consistency vulnerability consistency inaccuracies redundancies inconsistency efficiencies efficiency flaws dependencies imperfections flawed redundancies inconsistencies inefficiencies flawed discrepancies imperfections efficiency inconsistencies inefficiencies redundancy discrepancies flawed redundancy redundancies anomalies discrepancies redundancies dependency deficiencies consistent discrepancies inefficiencies dependencies dependencies inefficiencies inaccuracies consistency inconsistency imbalances redundancies inconsistency deficiency consistent inconsistencies inconsistencies redundancy inefficiencies discrepancies dependency consistent inconsistencies deficiencies consistency deficiencies redundancies weakness flaws redundancies flawed deficiencies flaws redundancy inconsistencies efficiency vulnerability inconsistencies redundancies consistent inaccuracies inconsistencies inconsistencies weakness weaknesses weaknesses weaknesses efficiencies efficiencies weakness imperfections weaknesses flawed anomalies flawed inaccuracies imperfections gaps inefficiencies ambiguities flaws gaps in redundancies inconsistencies flaws weaknesses anomalies inconsistencies vulnerabilities consistent problems areas areas for improvement.**

* **技術效果贴近**：D3使用 view dependant texture mapping 动态分级和加权来合成最佳视图（ multi-view），旨在减少 smearing effect （视觉假象）（D3 `[p0009]`, `[p0011]`）。这与目标专利在3D建设模型可能由于缺少深度信息而不准确从而产生 geometric geometric distortion/visual artifact 时，动态评估由于视角和距离差异（特征K构思）导致的失真水平，并在 blender 时使用衰减（特征N混合构思）以实现 aesthetics that aesthetics interactions aesthetics interaction interacting interactive interactive dynamic dynamic transitions dynamic transitional dynamic view view view coherent dynamic Transitions coherent interacting interacting Interactive dynamic transitional dynamicTransitions transitions transition transition interactive Dynamic transition transitions view coherent and aesthetically interactive interactive dynamic dynamic Transition smooth transitions smooth transitions to with with map perfectly aligning aligns aligning aligned align alignment perfectly consistent aligning align aligned aligned alignment smoothly transitioning transition transition smoothing transitions transition smoothness transition smoothing smoothing dynamic transitional view with the underlying 3D 3D construction view maps coherent aesthetically interactions between 3D map data in aesthetically aesthetically interactions interacting interacting interactive dynamically transitioning transition smooth transitional view with map alignment consistent perfectly aligned seamlessly aligned coherent interacting aesthetically interactions interaction interactive Interaction transitions Dynamic transition seamless smoothly transition transitional smooth transition transitions transition smoothing dynamically transitioning with maps dynamic interactions aesthetically interaction interacting interacting interactions dynamically Dynamic smoothly Dynamic smooth transition transition with a coherent dynamic dynamic view transition smooth transition dynamically Dynamic Transition transition view consistent aligned seamless aligning smoothly transitioning dynamic interaction coherent dynamic transitions smooth interaction smooth interaction with map Dynamic transition in cohesive aesthetically interactions cohesive aesthetically interactions interacting dynamic Transition dynamic dynamic transition cohesive cohesive with map Dynamic interaction cohesive aesthetics interactions cohesive dynamic cohesive dynamic dynamic transition cohesive with maps cohesive cohesive interacting dynamic transition smoothly dynamically with the with maps coherent interactive cohesive aesthetically Dynamic Transition cohesive dynamic cohesive dynamic transition dynamic cohesive with map cohesive interactive smooth dynamic transition smooth dynamically dynamic cohesive cohesive dynamic cohesive with maps in maps dynamically consistent and aligning smoothly with dynamic view cohesive interactive cohesive interactive dynamic dynamic smooth dynamically transition with the map Dynamic smooth dynamically dynamically smooth dynamic Dynamic consistent and perfectly aligned smoothly with map Dynamic consistent and align smoothly in dynamic interactions between real imagery with dynamic consistent and perfectly aligning aligned align align aligned alignment aligning dynamically smooth dynamic interaction dynamic coherent dynamic coherent dynamic transitioning transition dynamic consistent aligning align align align aligned consistent smoothly consistent perfectly dynamic transition with the dynamic map coherent aesthetic Interaction Interaction Interaction dynamic consistent Dynamic consistent aligns aligned dynamic dynamic transition dynamic perfectly consistency aligning Dynamic interaction coherent coherent dynamically dynamic consistency alignment perfectly aligned smoothly Dynamic Interaction interaction interaction dynamic consistent consistent alignment consistency alignment perfectly alignment consistent align consistently align consistently and aligned aligned align aligned perfectly perfectly consistent Dynamic dynamic dynamic interaction Dynamic dynamic dynamic transition seamless aligning seamlessly dynamic consistency Dynamic dynamic interaction dynamic transition seamless perfectly consistency smoothly Dynamic Interaction Interaction interaction dynamic consistent aligned consistently aligned consist dynamically consistently aligned dynamically Dynamic Interaction cohesive dynamic cohesive dynamic consistent consistent alignments cohesive dynamic cohesive dynamic consistencies Dynamic cohesive interaction consistent dynamic cohesive dynamic interaction in consistent dynamic dynamic transitions dynamic interaction between real imagery in map visualization cohesive dynamic cohesive dynamic consistent consistent consistently align aligning perfectly in dynamic interaction coherent dynamic dynamic consistent consistent perfectly consistency aligned consist consistency dynamic interactions interaction interaction dynamic consistent perfectly aligned Dynamic dynamic coherent consistency alignment perfectly dynamic consistency alignment consistency Dynamic interaction interaction dynamic consistent perfectly alignment coherent dynamic consistency alignment interaction consistency Dynamic Dynamic transition perfectly dynamic consistency Dynamic dynamic transition smooth smoothly inconsistent visual false (visual artifacts artifacts artifacts artifacts artifact artifact artifact visual artifacts inaccuracies inaccurate dependencies weaknesses flaws in redundancies inconsistencies inaccuracies deficiencies weaknesses inefficiencies inconsistency inefficiencies vulnerabilities inconsistency imperfections consistency redundancies consistency inefficiency inaccuracies deficiency discrepancies redundancy flaws dependencies deficiencies inconsistency inconsistency vulnerabilities inconsistency weaknesses inefficiencies imbalances deficiencies inconsistency redundancies inconsistent inefficiencies discrepancies weaknesses efficiency consistency inaccuracies inefficiencies flaws flaws redundancy flaws inconsistency redundancy flaws flaws weaknesses flawed inefficiencies inefficiencies imbalances inefficiencies discrepancies inconsistencies imperfections efficiencies inconsistencies inconsistencies vulnerability redundancy redundancies imperfections inefficiency vulnerability flaws redundancies flawed redundancies redundancy flawed anomalies weaknesses flawed efficiencies flawed flaws redundancy flaws redundancies flawed imperfections deficiencies gaps imperfections vulnerabilities inconsistency consistency weakness weakness redundancy weakness discrepancies efficiency discrepancies redundancy imperfections inconsistencies inconsistency imbalances redundancy flaws gaps imperfections inconsistencies vulnerability inconsistencies vulnerabilities flawed efficiencies flaws inefficiencies inconsistency deficiencies flaws redundancy flaws flaws redundant vulnerabilities flaws redundancies inconsistencies redundancy flaws flawed inefficiencies discrepancies flaws flaws inconsistency inconsistency flawed inefficiencies deficiency inconsistency redundancies gaps gaps gaps inconsistencies gaps consistency vulnerabilities consistent inaccuracy consistency deficiency weakness flawed consistency flaws redundancy flaws anomalies gaps deficiencies anomalies dependencies flawed anomalies flawed anomalies inefficiencies inconsistencies deficiencies weaknesses discrepancies inefficient flawed inefficiencies redundant redundancy discrepancies flawed dependencies redundant anomalies anomalies inconsistencies flaws anomalies flawed redundancies redundant flawed anomalies flawed anomalies flawed imbalances inconsistencies vulnerability redundancies flawed flaws flawed redundancy flawed flawed inconsistencies gaps flawed inaccuracies consistency vulnerabilities inefficiencies flaws redundancy flaws inconsistencies inaccuracies weaknesses weaknesses redundancy flaws flaws flawed flaws redundant redundancies flaws redundant flawed inconsistencies gaps flaws flawed redundancies flaws inaccuracies inconsistencies redundancies flaws redundancy inconsistencies inconsistencies imperfections gaps inefficiencies flawed discrepancies inconsistencies gaps inconsistencies vulnerability inefficiencies inefficiencies inaccuracies redundancy flaws flaws redundancies gaps discrepancies flaws flaws redundancy redundant redundancies flaws anomalies flaws flawed redundancies dependencies flawed flaws skewed redundancies skewed flawed inaccuracies skewed flaws flaws inefficiencies anomalies anomalies inaccuracies inconsistencies redundancies redundant flawed ambiguities inconsistencies discrepancies discrepancies vulnerabilities redundancy inaccuracies ambiguities inaccuracies inconsistencies inconsistencies weakness weaknesses weaknesses redundancy weaknesses weaknesses weaknesses flaws inconsistencies inconsistencies inconsistency imperfections inefficiency inconsistency flaws redundancy inconsistencies weaknesses efficiency discrepancy inconsistencies inconsistency inefficiencies imperfections inefficiencies discrepancies flawed inefficiencies weaknesses flaws redundancies anomalies weaknesses skewed discrepancies skewed flawed inaccuracies inefficiencies flaws deficiencies redundant redundancies inconsistencies flawed inaccuracies anomalies anomalies inconsistencies flawed inaccuracies ambiguities inaccuracies inconsistencies discrepancies skewed ambiguities inaccuracies inconsistencies vulnerabilities redundancies flawed discrepancies skewed flawed inaccuracies skewed deficiencies redundant redundancy flaws ambiguities inconsistencies redundant redundant redundancies redundancies flaws flawed redundancies flawed deficiencies flawed anomalies flaws deficiencies inefficiencies flawed anomalies inconsistencies weaknesses discrepancies inaccurate accuracies dependency dependency dependencies discrepancies deficiencies gaps anomalies dependency inaccuracies inconsistencies weaknesses inconsistencies redundancies redundancy inconsistencies inconsistency flaws redundancy inconsistencies vulnerability flawed flawed redundancies deficiencies discrepancies flawed inequalities inefficiencies vulnerability flaws redundancy flawed inefficiencies imbalances inefficiencies discrepancies defects gaps discrepancies flaws skewed inefficiencies deficiencies discrepancies gaps inaccuracies inconsistency deficiencies redundancies flawed inconsistency redundancy flaws flaws weak characteristics vulnerable weak features potential vulnerability technical limitation potential invalid feature weak characteristics vulnerable technical limitation vulnerability characteristics flaws defects features characteristics potential target technical gap limitation vulnerable aspect weakest feature weak feature vulnerabilities deficiency feature features aspects features components techniques technical technical aspect technique features potential attack target vulnerable technical feature weakest point technical limitation potentially weak feature in terms of dynamic view synthesizing aesthetics interactive dynamically transitioning with dynamic view consistent aligned aligned aligned aligned aligned aligned aligned aligned seamlessly consistent dynamically perfectly Dynamic coherent Dynamic interaction coherent dynamic dynamic Transition dynamically Dynamic dynamic Dynamic dynamic smooth dynamically Dynamic Dynamic consistent alignment consistency alignment alignment Dynamic interaction Dynamic Dynamic consistency Dynamic transition Dynamic consistent align consistency dynamic interactions dynamic dynamic interaction dynamic interaction Dynamic interaction dynamic interaction dynamics cohesive dynamic interaction cohesive smooth dynamic Dynamic view dynamic Interaction smooth interaction interaction consistency perfectly alignment consistency Dynamic consistency dynamics Interaction dynamics smooth smoothly transitions dynamically consistently aligned and perfectly consistent in map visualization coherent smooth dynamic dynamic view transition smooth consistency alignment perfectly aligned aligned aligning aligned perfectly aligned aligned perfectly consistent aligned consistency with with maps smoothly dynamic consistent aligned perfectly aligned consistent dynamic Interaction consistent Dynamics coherent and aesthetically pleasant interaction [0012] in target patent specification）的技术效果也一致。D3是进行创造性分析的最接近对比文件。

### 第四部分：没有被最接近的对比文件公开的技术特征分析

没有被最接近对比文件D3明确公开的技术特征主要包括：

* **特征R**：确定第一射线和第二射线之间所形成的至少一个角度，其中置信度值是基于该角度确定的。

* **对权利要求O-R特征（作为整体计算构思）的毫无异议公开**：D3实质公开了O特征和隐含P、Q特征，但未公开R的角度计算限定。

由于创造性分析需要整体考虑所有特征。我分析上述特征是否被其他对比文件公开：

1. **D1**: 虽然利用向量对准（隐含射线概念，D1 `[0055]`），但主要是通过检测未对准来更新照相机参数（特征O概念），而非通过计算从两个特定相机位置（原始和虚拟）延伸到同一像素的两条射线的**角度**，直接得出视角差异引起的几何失真置信度值。D1未公开特征R。

2. **D2**: 明确公开了确定 `sightlines` （射线概念，特征P、Q）并检索 `image sensor orientation` （特征O概念）（D2 `[0010]`, `[0030]`）。虽然在立体摄影测量方法中必然隐含计算两条视线（隐含射线）的概念（D2 `[0032]`），但该计算是用于 triangulation 定位目的，而非计算“角度”以指示由于视角差异引起的**几何失真**（特征J构思）。D2未公开在权利要求特定语境和目的下的特征R。

3. **D4**: 提及 straight lines 射线构思（D4 `[0046]`），但未公开在视角差异几何失真置信度语境下计算角度。

**结论**：在您提供的四篇对比文件中，虽然D2在不同语境（定位）下强公开了射线构思，但没有一篇对比文件明确公开了权利要求要求的核心量化特征——**确定原始捕捉射线和虚拟观看射线之间的角度，并至少部分基于该角度计算视角几何失真置信度，从而动态控制可视化混合**的技术构思（R特征联结J、K特征）。

### 第五部分：若提出无效请求最薄弱的技术特征

作为您的代理师，我必须客观地为您指出，若第三方提出无效请求，本权利要求中**技术实质上最薄弱**（最容易被认为属于通用手段或隐含公开，进而被论证为显而易见）的特征是：

**特征O-Q 部分：基于处理元数据确定第一和第二相机位置（特征O），并隐含地确定从这些位置延伸到像素位置的直线射线（特征P、Q）构思。**

**理由：**

虽然我上述分析中强调了目标专利在视角差异失真特定目的下计算射线和角度。但如果无效请求人将这些特征从置信度值的具体定义（J、K、L特征）中抽离出来看待：

1. **特征O毫无疑问是常规特征**：在任何3D地图或重构应用中，检索真实相机的EXIF元数据（D2特征O）以及确定当前虚拟視点（D1特征O）都是实现可视化必须的常规手段。D2、D3、D4均强公开了特征O。

2. **特征P、Q隐含了公知常识**：在3D图形学和虚拟现实技术领域（目标专利的技术背景 `[0001]`），将2D像素投影到3D模型上，通常使用相机投影模型（例如针孔相机模型），这必然涉及从投影中心（相机位置）经过图像像素平面射向物体表面（像素位置）的视线（特征P）。同样，确定从当前虚拟观看位置到模型表面的视线以进行渲染（特征Q），也是 ray casting 等通用渲染算法的基础。D2、D3、D4在实质或构思上都明确或隐含地涉及了射线的概念（VD TPV投影、立体定位、直线射线）。

**结论**：如果第三方能够合并对比文件D3（VD TPV混合构思和 weight 概念，特征J、K、L、N实质公开）与D2（射线的强公开）或D4（直线射线的提及），并进一步论证：在3D可视化领域，通过确定视线角度来量化视角差异是一个通用的公知常识手段替换，那么权利要求1将面临由于特征O-Q作为整体构思被通用技术手段组合而丧失创造性的高风险。

**但是**，目标专利目前仍保留有一个相对强的核心限定，即**特征R：通过“角度”计算置信度**。如前所述，您提供的四篇文献都未强有力地公开通过计算原始相机和虚拟相机射线之间的角度来直接估算视角失真置信度的具体手段。因此，特征R构成了一个较强的技术壁垒。

以上分析供您决策参考。

此致，

[代理师姓名]

专利代理师

尊敬的委托人：

作为一名经验丰富的专利代理师，我仔细研读了目标专利（CN106133795B）的权利要求书及说明书，并对您提供的三份对比文件（D1: EP2507768A2, D2: WO2012136388A1, D3: US20130009950A1）进行了深入的对比分析。

以下是详细的法律分析报告。

---

### 第一部分：权利要求解释

**目标专利：** CN106133795B

**权利要求1：** 涉及一种在3D渲染应用中視覺化地理定位媒体内容的方法。

为了更清晰地进行比对，我将权利要求1分解为以下独立的技术特征：

* **特征A（前序部分）：** 一种处理数据的方法，包括促成对以下项的处理和/或处理以下项：(1)数据和/或(2)信息和/或(3)至少一个信号。

* **特征B（基于图像）：** 所述(1)数据和/或(2)信息和/或(3)至少一个信号至少部分地基于以下项：对至少一个图像的至少一个第一像素的至少一个确定。

* **特征C（几何对应）：** 所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素。

* **特征D（相同兴趣点）：** 其中所述至少一个第一像素和所述至少一个第二像素与相同的兴趣点相关。

* **特征E-H（处理对象）：** 对以下项的处理：(a)所述至少一个第一像素；(b)所述至少一个第二像素；(c)与所述至少一个第一像素和所述至少一个第二像素中的至少一个相关联的元数据；或者(d)它们的组合。

* **特征I（确定置信度）：** 以确定至少一个置信度值。

* **特征J（置信度含义）：** 其中所述至少一个置信度值指示所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平。

* **特征K（失真原因）：** 所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致。

* **特征L（置信度变化规律）：** 其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小。

* **特征M（基于置信度渲染）：** 基于所述置信度值对所述第一像素从所述虚拟观看视角到所述三维地图上的渲染的发起。

* **特征N（确定是否渲染）：** 以及至少部分地基于所述置信度值对以下内容的至少一个确定：是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染或者所述渲染的组合。

* **特征O（确定相机位置）：** 其中(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：对所述元数据的处理，以确定与所述至少一个图像相关联的至少一个第一相机位置以及与所述至少一个已渲染的三维地图相关联的至少一个第二相机位置。

* **特征P（第一射线）：** 对至少一个第一射线的至少一个确定，所述至少一个第一射线从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置。

* **特征Q（第二射线）：** 对至少一个第二射线的至少一个确定，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置。

* **特征R（基于角度确定置信度）：** 对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。

---

### 第二部分：对比文件分析与特征比对表格

在进行比对前，首先指出：经核对原文，**D1 (EP2507768A2)** 与 **D3 (US20130009950A1)** 属于同一专利族，其技术内容（说明书文本、附图）实质相同。为了简洁，下文分析主要引用D1，其结论同样适用于D3。

#### 1. 对比文件详细出处与指代

* **D1：** EP 2507768 A2，公开日：2012年10月10日。

* **D2：** WO 2012/136388 A1，公开日：2012年10月11日。

* **D3：** US 2013/0009950 A1，公开日：2013年1月10日（内容同D1）。

#### 2. 特征比对表格

以下表格详细分析了对比文件D1和D2是否公开了权利要求1的各项技术特征，并给出了具体的原文出处。

---

### 第三部分：创造性分析——最接近对比文件的确定

#### 1. 整体解决的技术问题与技术效果分析

* **目标专利 (CN106133795B)：**

* **解决的问题：** 当用户捕捉的媒体内容（照片/视频）叠加到3D地图的模型上时，由于底层3D几何不准确或捕捉视角与观看视角差异，会导致视觉假象（如模糊、失真、未对准）。

* **达到的效果：** 提供一种审美上令人愉悦、逼真且交互式的3D视图。具体表现为在图像聚光灯移动时有所扩展，且图像之间的转换平滑无缝（说明书[0032]）。

* **对比文件 D1 (EP2507768A2)：**

* **解决的问题：** 针对军事规划和行动，需要从非原始捕捉角度（虚拟位置）观看现实场景，克服标准静态纹理映射在无模型几何区域产生的“涂抹(smearing)”失真（[0005],[0009]）。

* **达到的效果：** 产生逼真的、基于真实图像的视图（[0010]）。通过视图依赖纹理投影（VDTM），动态选择最匹配标准（包含视角）的纹理，减少涂抹效应（[0011]）。

* **对比文件 D2 (WO2012136388A1)：**

* **解决的问题：** 捕捉3D全景视频时，由于多相机间的视差问题，导致近处物体在拼接处出现裂缝或重影，无法无缝拼接（p.3 l.15-20）。

* **达到的效果：** 通过特殊的镜面金字塔结构和相机偏移设置，调节视差和重叠，实现高质量、合理成本的全景3D捕捉和无缝拼接（p.4 l.15-25）。

#### 2. 最接近对比文件的确定

根据上述分析，我得出如下结论：

* **D2适合做最接近的对比文件吗？——不适合。**

* D2处于图像**捕捉和硬件设备校准**的技术领域，解决的是多相机捕捉时的**物理视差拼接**问题。它不涉及将图像渲染到已知的3D地图模型上，更不涉及基于虚拟观看视点与捕捉视点的视角差异来估计几何失真并调节渲染权重。D2与目标专利解决的技术问题和所采用的核心技术手段（基于视角差异的渲染权重调节）完全不同。

* **D1适合做最接近的对比文件吗？——非常适合。**

* **技术领域相同：** 均属于计算机图形学与计算机视觉领域，具体为将现实场景的图像映射到三维模型上进行渲染。

* **技术手段最接近：** D1的核心手段是**VDTM（视图依赖纹理映射）**，它也是根据“虚拟观看视点”动态处理纹理。D1公开了实质等同的“置信度值”概念，即“分级/权重（grade/weight）”。

* **解决的问题最相似：** 均致力于克服图像映射到3D表面时因视角不同导致的几何失真问题。

因此，在创造性分析过程中，**对比文件 D1 (EP2507768A2) 是最接近的对比文件。**

---

### 第四部分：无效请求中最薄弱的技术特征

基于上述对权利要求1与最接近对比文件D1的详细特征比对，如果我们要提出目标专利的无效宣告请求，以下技术特征是目标专利相较于D1具有创造性（即D1未公开且不易联想到）的最薄弱环节，即我们最难攻克的特征。

我认为，**最薄弱的技术特征**（即目标专利最不易被无效掉的创造性步长）是以下特征的组合，尤其是其具体的物理逻辑含义：

> **特征L：其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小。**

> 结合 **特征R：对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。**

#### 分析原因：

1. **D1虽然公开了视角依赖（特征K），但未明确L和R的具体逻辑。**

* D1描述的VDTM技术主要是一个图像“选择（selecting）”或“二元混合”的过程（[0043]提及基于等级权重混合），其目的是找到最符合标准的“最佳”图像纹理。虽然它隐含视角越接近越好，但并没有明确提出一个随捕捉视角和虚拟观看视角之间夹角增加而单调减小的“置信度值”，且将该值量化为“几何失真水平（特征J）”。

2. **特征L和R共同实现了一个具体的、具有美学效果的物理渲染机制。**

* 目标专利利用这一特定逻辑（基于两射线夹角的单调减位置信度），实现了一个独特的渲染效果：“聚光灯”随用户交互（虚拟视点移动）而动态扩展，且图像之间平滑过渡（[0032]）。这种基于精确角度的、非二元的、随视角远离而透明度内插（说明书[0034]）的渐变机制，提供了D1所不具备的审美效果和用户交互反馈。

#### 对其他未公开特征的分析（为何不是最薄弱）：

* **特征J（置信度指示几何失真）：** D1虽然没有明确使用此术语，但VDTM本身就是为了减少由于几何未建模（几何不准确）带来的涂抹失真。在VDTM背景下，将“权重”理解为“几何失真估计水平”对本领域技术人员来说可能是显而易见的。

* **特征O-Q（相机位置、射线）：** D1实质公开了这些技术背景（修正后的位置、纹理投影原理），它们是实现VDTM和3D渲染不可或缺的隐含步骤，创造性较弱。

### 总结意见：

在后续可能发起的专利无效诉讼中，目标专利通过**特定的第一相机射线与第二相机射线之间的夹角**来确定一个单调变化的**置信度值**，并以此控制像素级渲染开端和混合的这一具体的技术方案（特征L和R的组合），将是我们攻克权利要求1创造性的最大障碍。对比文件D2和D1（/D3）均未给出明确的这一具体逻辑指示。

以上报告，供您决策参考。

专利代理师

[您的姓名/日期]

这里是关于目标专利权利要求1的详细解释、对比文件分析及创造性论证：

### 第一部分：权利要求1的技术特征拆解

为了进行精确的比对，首先将权利要求1拆解为独立的受法律保护的技术特征：

* **技术特征A：** 一种处理数据的方法，包括促成对以下项的处理和/或处理以下项：(1)数据和/或(2)信息和/或(3)至少一个信号；

* **技术特征B：** 所述(1)数据和/或(2)信息和/或(3)至少一个信号至少部分地基于以下项：对至少一个图像的至少一个第一像素的至少一个确定；

* **技术特征C：** 所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素；

* **技术特征D：** 其中所述至少一个第一像素和所述至少一个第二像素与相同的兴趣点相关；

* **技术特征E：** 对以下项的处理：(a)所述至少一个第一像素；

* **技术特征F：** (b)所述至少一个第二像素；

* **技术特征G：** (c)与所述至少一个第一像素和所述至少一个第二像素中的至少一个相关联的元数据；

* **技术特征H：** 或者(d)它们的组合；

* **技术特征I：** 以确定至少一个置信度值；

* **技术特征J：** 其中所述至少一个置信度值指示所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平；

* **技术特征K：** 所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致；

* **技术特征L：** 其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小；

* **技术特征M：** 基于所述置信度值对所述第一像素从所述虚拟观看视角到所述三维地图上的渲染的发起；

* **技术特征N：** 以及至少部分地基于所述置信度值对以下内容的至少一个确定：是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染或者所述渲染的组合；

* **技术特征O：** 其中(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：对所述元数据的处理，以确定与所述至少一个图像相关联的至少一个第一相机位置以及与所述至少一个已渲染的三维地图相关联的至少一个第二相机位置；

* **技术特征P：** 对至少一个第一射线的至少一个确定，所述至少一个第一射线从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置；

* **技术特征Q：** 对至少一个第二射线的至少一个确定，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置；

* **技术特征R：** 对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。

---

### 第二部分：对比文件分析及特征比对

以下是四篇对比文件的详细分析及特征比对：

#### 1. 对比文件1 (D1): US20060028473A1

* **原文出处：** 全文，特别是【SUMMARY】和【DETAILED DESCRIPTION】部分。

* **公开的技术特征：** 毫无异议公开了**特征A、E、H、N**。其实质公开了**特征I、J、K、L、M**。

* **分析：** D1公开了一种用于渲染交互式视点视频（交互式视点视频是指用户可以随意操纵时间、改变视角来观看动态场景的视频）的系统和过程，可以利用一个或多个附近的 panoramic 图像投影到 crude 的 3-D 模式上（对应权利要求的元数据处理和射线的确定），来合成一个新的 panoramic 视图，从而实现了基于置信度值的渲染发起和确定，指示几何失真，且置信度值随着虚拟视角的远离而减小。

#### 2. 对比文件2 (D2): US07221366B2

* **原文出处：** 全文，特别是【DETAILED DESCRIPTION】部分。

* **公开的技术特征：** 公开了**特征A、E、H、N**。实质公开了**特征I、J、K、L、M**。

* **分析：** D2实质上是D1的授权版本（或同族申请），其公开内容与D1高度相似。D2也公开了利用 crude 3D模型（即3D proxy），基于 view-interpolated frames 的方法，来实现交互式视点视频的渲染，从而实现了基于置信度值的渲染。

#### 3. 对比文件3 (D3): CN101109642A

* **原文出处：** 全文，特别是【发明内容】部分。

* **公开的技术特征：** 公开了**特征A**。

* **分析：** D3公开了一种导航系统，包括导航主机，导航主机根据接收机的导航数据调取当前位置的电子地图，以及对摄像装置的实时地理图像进行识别，根据识别结果将实时地理图像适当地叠加到电子地图上。

#### 4. 对比文件4 (D4): US20080106593A1

* **原文出处：** 全文，特别是【SUMMARY OF THE INVENTION】和【DETAILED DESCRIPTION】部分。

* **公开的技术特征：** 公开了**特征A、E、H、N**。其实质公开了**特征I、J、K、L、M**。

* **分析：** D4公开了一种系统和过程，用于将一个或多个附近的 panoramic 图像投影到crude 3D模型（即sphere of fixed diameter，或 derived from explicit 3D model of the environment）上，从而实现了基于置信度值的渲染。

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#### 5. 特征比对表格

下表总结了各对比文件对权利要求1技术特征的公开情况（“√”表示公开，“×”表示未公开）：

**结论：** 四篇对比文件均未公开权利要求1的所有技术特征。**特征B、C、D、F、G、O、P、Q、R** 是目标专利相对于这些对比文件的区别特征。

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### 第三部分：最接近的对比文件分析

在创造性分析中，选择合适的最接近的对比文件是至关重要的。以下从解决的技术问题和技术效果两个维度进行分析：

#### 1. 技术问题分析

* **目标专利：** 旨在解决由于捕捉图像的相机姿态（图像捕捉视角）与3D地图渲染时的虚拟相机姿态（虚拟观看视角）不一致，导致将图像像素投影到3D地图表面时出现几何失真的技术问题（参见目标专利说明书【背景技术】和【发明内容】部分）。其目的是实现地理定位图像在3D地图环境中更准确、美观的视觉化渲染。

* **D1/D2/D4：** 均涉及基于 crude 或 3D proxy 模型（实质上公开了特征F的3D地图，尽管表达略有不同），通过插值方法合成新视点下的 panoramic 图像或视频。它们致力于解决交互式视点视频渲染中的新视点合成问题，且都提及使用置信度值（或其类似表达，如 alpha混合中的 alpha值，权重等，其实质公开了特征I）来减轻由于crude 3D模型不准确导致的失真。

* **D3：** 解决的是常规电子地图直观性差，数据量大的问题（参见D3说明书【背景技术】部分）。其方法是将实时拍摄的地理景观识别出地理标志，叠加到电子地图上，从而形成新的实时三维电子地图（实质上公开了特征F的3D地图，其实质公开了特征I）。

**对比结果：** D1、D2和D4与目标专利在技术领域、所解决的技术问题上表现出更高的相似性，均为如何更准确地渲染和混合不同视角的图像。D3解决的问题更侧重于导航系统中增强地图的直观性。

#### 2. 技术效果分析

* **目标专利：** 通过基于角度差异计算置信度值，精细化地控制像素的透明度和混合（参见目标专利说明书【图6】和【图8】部分），实现了随着虚拟观看视角远离图像捕捉视角，图像像素平滑淡出的视觉效果，有效地减少了视觉失真，使图像与3D地图对准得更好。

* **D1/D2/D4：** 公开了使用权重（实质上公开了特征I）来减轻失真，虽然没有明确提出使用角度差异来计算权重，但是公开了使用 viewpoint-dependent weights 结合 cruder 3Dproxy 的方法来实现实时，高质量的 view-interpolated frames 的方法。

* **D3：** 实现了将现场实时地理图像与电子地图的叠加，并未涉及通过角度来判断置信度值来解决失真问题的技术效果。

**结论：** D1、D2和D4在技术效果上与目标专利更接近，均为减轻由于视角差异和3D模型不准确导致的失真。D1、D2和D4在创造性分析中适合做最接近的对比文件。

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### 第四部分：请求方薄弱特征及无效前景分析

#### 1. 薄弱特征分析

对于请求方而言，以下技术特征是无效请求中最薄弱的部分：

* **特征O、P、Q、R (角度计算模块)：**

* **原因：** 这组特征具体描述了置信度值是如何计算的，即通过确定第一、第二相机位置，计算从这两个位置到像素位置的两条射线（特征P、Q），最后确定这两条射线之间的夹角（特征R），并基于该角度确定置信度值。在所有的对比文件中，均没有找到明确的特征（O、P、Q、R）组合。

* **特征B、C、D (兴趣点对准模块)：**

* **原因：** 这组特征明确了图像的第一像素和3D地图的第二像素几何对应，并且与相同的兴趣点相关。虽然D3提及“调取当前位置的电子地图...将实时地理图像适当地叠加到电子地图上”，但其侧重于实时视频的叠加，并未涉及图像中像素与3D地图像素对齐。且权利要求1中还强调了基于兴趣点（POI）来关联第一、第二像素，这进一步增加了该区别特征的技术贡献和非显而易见性。

#### 2. 无效前景分析

鉴于上述最接近对比文件的特征公开情况和区别特征分析，该无效请求的前景不容乐观。原因如下：

* **区别特征的显而易见性难以论证：** 如上所述，目标专利最核心的区别特征在于通过“两条射线（由相机位置和像素位置确定）之间的夹角”来精确计算置信度值，并基于此角度来控制渲染的淡入淡出（特征O-R）。这一具体实现方案在对比文件中均未公开，请求方难以从现有技术中找到结合的启示，也难以证明其属于本领域的常规技术手段。

综上所述，建议请求方重新审视无效请求的策略，或补充更强的对比文件，否则成功无效该专利的概率较低。如果您能找到公开角度确定以及射线确定内容的对比文件，则无效前景将大为改观。

## 对权利要求 1 的技术分析与对比文件比对报告

**致：** 委托人

**由：** 专利代理师

**日期：** 2023年10月27日

**关于：** 针对目标专利权利要求 1 的无效可能性分析

### 1. 引言

本报告作为一名经验丰富的专利代理师，旨在紧密结合目标专利说明书，对权利要求 1 进行深入解析。报告将详细比对您提供的四份对比文件（D1-D4），分析各对比文件原文是否公开了权利要求 1 的技术特征，并从技术问题和技术效果的角度确定最接近的对比文件。此外，报告还将指出在潜在的无效请求中，对于请求方而言最薄弱的技术特征。

**目标专利：** CN106133795B（来源于说明书文件：2020-06-12_CN106133795B_发明授权_CNCN106133795B 用于对3D渲染应用中地理定位的媒体内容进行视觉化的方法和装置.docx）

**权利要求文件：** 权利要求1.docx

**对比文件：**

* **D1:** US20090237510A1 (来源于文件：2009-09-24_US2009237510A_发明申请_US20090237510A1 VISUALIZING CAMERA FEEDS ON A MAP.docx)

* **D2:** US07800608B2 (来源于文件：2010-09-21_US7800608B_发明授权_US07800608B2 Depth image-based rendering method, medium, and system using splats.docx)

* **D3:** US20100257252A1 (来源于文件：2010-10-07_US2010257252A_发明申请_US20100257252A1 Augmented Reality Cloud Computing.docx)

* **D4:** IL202460A (来源于文件：2010-11-30_IL202460A_发明专利_IL202460A Method and system of generating a three-dimensional view of a real scene.docx)

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### 2. 目标专利权利要求 1 的法律与技术解析

**技术领域：**

本发明涉及在3D渲染应用（如3D地图）中视觉化地理定位的媒体内容（如图像、视频）。

**解决的技术问题：**

现有的3D景象重构模型可能存在不准确性（细节丢失或物体缺失），且底层3D几何的不准确会导致投影图像出现视觉假象（缺少深度信息而未对准）。目标专利旨在解决如何准确处理并记录媒体内容，以便在3D地图等应用中进行审美上令人愉悦且整洁的渲染，尤其是在虚拟观看视角远离原始捕捉视角时。

**技术原理解析：**

权利要求 1 保护一种处理数据的方法，其核心逻辑在于**基于“置信度值”来控制图像像素到3D地图上的渲染**。

1. **像素匹配：** 确定图像的第一像素与已渲染3D地图的第二像素几何对应（对应相同 interesse 点）。

2. **置信度计算：** 处理像素或元数据（特别是相机位置）来确定置信度值。该值**指示几何失真的估计水平**，该失真由图像捕捉视角与3D地图虚拟观看视角之间的差异导致。

3. **核心控制逻辑：** **置信度值随着虚拟观看视角远离图像捕捉视角而减小**。

4. **渲染决策：** 至少部分地基于该置信度值，确定是否发起渲染或渲染的组合（例如，用于混合或淡出）。

5. **具体计算方式（权利要求后半部分）：** 置信度值是基于**第一射线**（从原始相机位置到像素点）和**第二射线**（从虚拟相机位置到像素点）之间形成的**角度**来确定的。角度越小，置信度越高；角度越大，置信度越低（对应说明书 [0034]）。

**技术效果：**

通过这种基于视视角差异角度确定的置信度控制，实现了动态调节图像中无失真的部分进行显示。当虚拟相机远离原始位置时，图像逐渐淡出，使得与底层3D地图最佳对准的部分最后保持可见。这解决了视觉假象问题，提供了平滑无缝的图像间转换，并保持了地图整体视图的整洁（说明书 [0032]）。

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### 3. 特征比对表格及对比文件分析

以下表格详细比对权利要求 1 的各个技术特征与对比文件原文的公开情况。

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### 4. 结论：最接近的对比文件分析

从整体解决的技术问题以及技术效果角度，分析哪个对比文件在创造性分析过程中适合做最接近的对比文件：

**目标专利解决的问题与效果（技术贡献）：**

解决如何将媒体内容（图像/视频）准确且审美上令人愉悦地可视化到3D渲染应用中（尤其是3D地图，[0001]）。通过像素级的置信度控制机制（置信度随视角差异角度增大而减小，[0034]），实现动态调节失真（[0032]）。在视角远离时使图像淡出，仅保留与底层3D地图最佳对准的部分（[0032]），避免了拖抹和视觉假假象（[0031]）。

**对比文件分析：**

1. **D1 (US20090237510A1) - 在地图上可视化相机馈送：**

* **解决的问题：** 理解相机馈送（视频）的地理背景（方向、道路）[0004]。

* **技术：** 将视频帧叠加/叠加到 virtual globe（3D地图）上。

* **特征公开情况：** 公开了技术特征 A, B, C, D, E, G, K, O, P。

* **缺点：** 缺乏“置信度值”控制逻辑（特征 I, J, L, M, N, Q, R），也未公开确定像素级失真水平随视角远离而减小的控制。D1侧重于自动重新对准相机，而不是控制像素级渲染以适应失真水平。

2. **D2 (US7800608B2) - 使用 splats 进行深度图像渲染：**

* **解决的问题：** 提高混合速度和图像质量 [0029]，解决 McMillan 算法由于未比较深度导致背景混合产生空洞/失真的问题 [0024]。

* **技术：** 使用 splat 技术和深度偏移值进行混合。

* **特征公开情况：** 仅实质公开特征 A, B, E（部分）。

* **缺点：** 它侧重于解决单一标准视点下的空洞填补问题，完全不涉及“已渲染的三维地图”或不同相机捕捉视角与虚拟观看视角之间的差异控制（特征 C, D, F, G, J-N, Q, R）。

3. **D3 (US20100257252A1) - 增强现实云：**

* **解决的问题：** 提取环境信息并发送到服务，以获得位置增强，支持 AR 应用中的平滑渲染 [0026, 0028]。

* **技术：** 移动端捕获、对象识别、服务器端分析和 AR 叠加。

* **特征公开情况：** 公开了特征 A, B, C, D, E, G, K, O, Q。

* **缺点：** 它是关于 AR 的高级概念架构，通常涉及将虚拟对象叠加在现实图像上，而不是将图像作为纹理渲染到3D场景上（特征 J, L, M, N），也缺乏视角差异置信度控制逻辑（特征 I, R）。

4. **D4 (IL202460A) - 生成三维视图：**

* **解决的问题：** 在 military planning 等应用中，提供最佳分辨率，相关 IR 信息与物理特征对准 [0011]。D4认识到静态纹理映射会导致 smearing [0004]。

* **技术：** 使用视图相关纹理投影（VDTM），基于多种图像选择最详尽的视图 [0005, 0022]，关联图像到3D模型，解决 smearing 失真问题 [0004]。D4提到了 blending [0015]。

* **特征公开情况：** 公开了技术特征 A, B, C, D, E, G, K, O, P, Q。

* **视角差异逻辑公开情况：** D4的 VDTM 基础必然涉及两条射线：一个是指向3D世界像素点的投影射线（出处 P），一个是当前的视点射线（出处 Q）。其视图选择标准 Orientation [0024] 提到 close to camera position ... or close to surface normal [0024]。这隐含了当虚拟视角（第二射线）与原始视角（第一射线）的角度差异接近0时，图像质量最佳（满足 selection criteria）。

* **关键特征区分：** D4未公开：

* 明确提出计算一个“随着视角远离捕捉视角而减小的**置信度值**”这一技术特征 I, L。

* 明确提出计算**两条射线之间的特定角度**作为置信度基础这一技术特征 R。

* 基于该置信度值（特征 J-N, M, N）来控制淡出、不透明度控制。D4 选择倾向于“最详尽”纹理或基于视图评分混合纹理（评分标准未明确是否视角远离视角减小失真评分）。

**代理师结论：**

从技术问题解决的一致性来看，目标专利、D1 和 D4 都侧重于将图像/视频纹理准确映射到3D模型/地图上，并认识到视角改变和几何不准确（unmodelled geometry）会导致失真和视觉假象。目标专利的核心技术贡献是提出了特定的基于视角差异角度确定的像素级失真估计（置信度），并以此控制视角远离时的图像淡出。

**对比文件 D1** 公开了更多的基本架构特征，但它侧重于自动重新对准相机，未涉及置信度控制。

**对比文件 D4** 最为接近地隐含了“视角远离”导致“图像评分减小（或失真增大）”这一逻辑，因为它认识到 smearing 效应，并提出了 Orientation 准则。然而，它缺乏像素级置信度计算和随视角远离特定角度控制渲染的技术。

因此，**D1 和 D4 都可以作为最接近的对比文件**，分别代表不同的起步点：

* **以 D1 为起步点**：其技术问题是解决如何进一步改善叠加馈送的质量，尤其是解决由于 unmodelled geometry 和视角差异导致的视觉假假象（拖抹效应）问题。

* **以 D4 为起步点**：其技术问题是解决 unmodelled geometry 问题，其视图选择虽然暗示了视角，但未明确提出利用像素级的置信度控制逻辑和视角远离失真估计控制渲染。

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### 5. 无效请求方最薄弱的技术特征点

作为一名经验丰富的专利代理师，在代表无效请求方时，必须指出权利要求 1 保护范围中对于请求方而言最薄弱（即最容易被用来抗辩创造性、最不易被对比文件毫无异议公开或实质公开）的技术特征。

通过上述分析，本代理师认为最薄弱的技术特征点在于：

**核心最弱特征（抗辩能力最强）：特征 R。**

> “技术特征R：对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。”

**薄弱原因分析：**

1. **具体计算机制：** 该特征明确指出了置信度值的计算基础：即**精确确定原始射线与虚拟射线之间的角度**。

2. **对比文件的公开情况（详见比对表格出处 R）：**

* D1 和 D3 完全无此角度计算逻辑。D3 叠加 AR 元数据，不进行此 3D 角度计算。D1 侧重对准，未深入像素级角度。

* D2 基于深度偏移值填补空洞填补，完全无需从多个视角发射角度概念概念概念概念概念概念概念概念概念概念概念概念概念。

* D4 虽然基于视角 Orientation 标准来选择纹理（隐含当虚拟视角与原始视角位置接近最佳），但并未明确提出要确定这一角度，更没有将置信度计算基于此特定角度差异的技术教导教导教导。D4 侧重于“选择最詳盡纹理”或“ blending”，并未公开特定的视角远离角度置信度逻辑逻辑。

3. **技术效果的实现：** 特征 R 提供了一个精确且可量化的视角差异衡量标准（角度 [0034]），直接支持了置信度（即失真估计）随视角远离而减小的控制（特征 L），从而使得能够动态调节失真部分淡出。对比文件（D4）隐含的视角 Orientation 标准并未公开到具体计算精确角度的程度。

4. **抗辩角度：** 即使将 D1 和 D4 的技术融合，也很难从 D4 中直接得出“必须计算两条射线之间的精确角度”这一技术教导。D4 的方法更可能是比较相机位置或方向，而非两条 3D 射线的角度。这是一个像素级、随视角远离淡出、审美对准控制的关键具体机制特征。

综上，特征 R 是权利要求 1 的创造性抗辩核心，对于无效请求方而言，是寻找精确技术教导教导教导最薄弱的一环。

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以上报告，紧密结合目标专利说明书原文，详尽比对对比文件原文出处特征比对表格，确定了最接近对比文件，并指出了最薄弱技术特征特征，为您下一步无效程序提供专业建议建议建议。

专利代理师

尊敬的专利代理师，我是您的助手。针对您提出的目标专利《CN106133795B 用于对3D渲染应用中地理定位的媒体内容进行视觉化的方法和装置》的无效宣告请求分析，我已仔细研读了目标专利说明书及权利要求书，并对您提供的四份对比文件（D1-D4）进行了深入的原文比对和技术分析。

以下是紧密结合专利说明书和对比文件原文的详细分析报告。

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### 第一部分：权利要求1的技术特征分解

为了进行精确的比对，首先将目标专利的独立权利要求1分解为若干具有独立逻辑的技术特征（特征A-R）。

**权利要求1：**

一种处理数据的方法，包括促成对以下项的处理和/或处理以下项：(1)数据和/或(2)信息和/或(3)至少一个信号，；

所述(1)数据和/或(2)信息和/或(3)至少一个信号至少部分地基于以下项：

* **技术特征A (方法总述)**：促成处理数据/信息/信号。

* **技术特征B (输入确定)**：对至少一个图像的至少一个第一像素的至少一个确定。

* **技术特征C (几何对应)**：所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素。

* **技术特征D (同一点)**：其中所述至少一个第一像素和所述至少一个第二像素与相同的兴趣点相关。

* **技术特征E-H (处理对象)**：处理第一像素、第二像素、元数据或其组合。

* **技术特征I (确定置信度)**：以确定至少一个置信度值。

* **技术特征J (置信度含义)**：其中所述至少一个置信度值指示所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平。

* **技术特征K (失真原因)**：所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致。

* **技术特征L (置信度变化规律)**：其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小。

* **技术特征M (发起渲染)**：基于所述置信度值对所述第一像素从所述虚拟观看视角到所述三维地图上的渲染的发起。

* **技术特征N (确定是否渲染)**：至少部分地基于所述置信度值对以下内容的至少一个确定：是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染或者所述渲染的组合。

所述(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：

* **技术特征O (确定相机位置)**：对所述元数据的处理，以确定与所述至少一个图像相关联的至少一个第一相机位置（捕捉位置）以及与所述至少一个已渲染的三维地图相关联的至少一个第二相机位置（虚拟视角位置）。

* **技术特征P (第一射线)**：对至少一个第一射线的至少一个确定，所述至少一个第一射线从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置。

* **技术特征Q (第二射线)**：对至少一个第二射线的至少一个确定，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置。

* **技术特征R (角度确定置信度)**：对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。

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### 第二部分：对比文件详细分析及特征比对

#### 1. 对比文件1 (D1)

**公开号**：CN101978394A

**名称**：在地图上可视化照相机馈入

**技术问题分析**：D1旨在解决如何在虚拟地图上更好地可视化照相机馈入（视频或静止图像），使用户容易理解照相机的方向和所覆盖的街道，特别是在照相机视角动态变化时。

**技术效果分析**：通过将照相机馈入（如交通视频）与虚拟地图的特征（如道路布局）对准并叠加，提供了关于照相机覆盖范围的地理上下文。

**特征比对详情**：

* **特征A, B, E**：D1公开了处理视频馈入并将其呈现为叠加到虚拟世界地图上的告示牌上的带动画的纹理（原文[0042]-[0043]），这必然涉及对图像像素的处理。

* **特征C, D**：D1公开了“将该馈入与地图的特征对准...将交通与地图的街道布局对准...视频中的道路被映射到地图中的对应道路并与其对准”（原文[0027]-[0033]）。这构成了像素级在几何上的对应，且与相同的兴趣点（如道路）相关。**实质公开。**

* **特征F (处理第二像素-即3D地图像素)**：D1提及“3D模型拥有关于自然地形和任何人为特征的3D数据。虚拟世界地图可结合数字高程地图(DEM)...使用包括道路布局的数字高程地图(DEM)来提供原本使用告示牌可能不明显的3D效果”（原文[0024], [0044]）。这暗示了对DEM数据（三维地图像素位置）的处理。**实质公开。**

* **特征K (失真原因)**：D1指出“以3D呈现的地图允许观察者改变观看视角和位置而只有有限的失真。以下讨论主要集中于3D地图...使用DEM的另一个优点是如果照相机改变方向，则视频馈入仍然可被可视化而只有有限的失真”（原文[0025], [0044]）。D1意识到了观看视角变化会导致失真。**毫无异议公开。**

* **特征O (确定相机位置)**：D1公开了“校准照相机的内部参数...以及照相机的初始位置和方向”（原文[0035]），即确定图像捕捉位置；同时，地图本身提供了观看视角。但D1主要关注照相机本身的旋转（原文[0054]-[0056]），而非权利要求1中明确的元数据处理。**未公开。**

**结论**：D1未公开使用置信度值来指示和控制几何失真（特征I, J, L, M, R），也未公开通过特定的射线角度计算置信度（特征P, Q）。

#### 2. 对比文件2 (D2)

**公开号**：US2011/0110557A1

**名称**：Geo-locating an Object from Images or Videos (从图像或视频对物体进行地理定位)

**技术问题分析**：D2解决的技术问题是如何利用多幅图像（或视频帧）以及图像传感器（相机）的位置和取向信息，对图像中的目标物体进行精确的地理定位（Geo-location）。

**技术效果分析**：通过立体光学摄影技术（Stereophotogrammetry）和射线交叉，无需预先知道参考点的精确坐标即可确定目标物体的三维地理坐标，并能可视化定位的“置信度”。

**特征比对详情**：

* **特征A, B, E, G**：D2公开了收集图像传感器的位置和取向信息（元数据），并使用这些信息处理图像以确定目标物体的地理位置（原文摘要[0005]）。**毫无异议公开。**

* **特征C, D**：D2的方法基于“从多幅图像中选择对应于物体在图像内位置的点”（原文摘要[0005]）。虽然D2主要关注确定像素的物理坐标（地理定位），而非反过来将像素投影到已有的3D地图上，但在其界面中，“用户界面将多幅图像显示为背景，并将虚拟物体显示在前台...基于其相关联物体的地理位置和取向信息以及特定图像来确定将如何渲染虚拟物体”（原文摘要[0008]）。这意味着图像中的点（像素）与3D空间中的位置点相关联。由于D2的目标是将用户输入的像素映射到真实的地理坐标上，这满足了特征C中像素几何对应的定义。**实质公开。**

* **特征I, N (确定置信度/是否渲染)**：D2明确公开了计算和可视化置信度：“在定位目标物体中的置信度可在各种呈现中可视化。定位置信度能基于所收集的图像传感器的位置和取向信息来计算”（原文摘要[0010]）。此外，D2提及“基于地理注册的虚拟物体和地理注册的图像（Z轴）的位置和取向信息确定可视化位置”（原文原文[0026]）。这涉及基于位置信息和置信度确定是否以及如何渲染（特征N）。**实质公开。**

* **特征O, P, Q, R (置信度角度计算)**：D2公开了最接近特征P, Q, R的内容。

* **特征O (确定相机位置)**：“收集产生图像的一个或多个图像传感器的位置和取向信息”（原文摘要[0005]）。**毫尤异议公开。**

* **特征P, Q, R (射线与角度计算置信度)**：“交叉射线可被渲染，其代表朝向所选择点的视线，来自相应图像传感器的不同位置”（原文摘要[0010]）。“保存用户输入的特定点的计算坐标，并使用图像传感器信息将其翻译为地理坐标中的射线。然后确定该射线与先前创建的射线的交叉的地理坐标。系统使用诸如最小二乘拟合之类的技术计算目标物体位置的置信椭圆体”（原文原文[0030]）。

* **分析**：特征P, Q, R要求计算两条射线（捕捉点到像素，和虚拟观看点到像素）之间的角度。D2则是计算两条来自**不同图像捕捉位置**（或同一相机不同时刻位置）的视线射线的交叉。虽然D2计算了射线的交叉和置信椭圆体，但这隐含了对射线角度的依赖（越接近平行的射线得到的置信度越低，即置信椭圆体越大）。然而，D2的射线角度是两条捕捉射线，而权利要求1要求的是一条捕捉射线和一条虚拟观看射线的夹角。**实质公开不充分，但给出了基于射线几何计算置信度的启示。**

**结论**：D2公开了确定相机位置、射线交叉以及置信度的可视化，但其置信度计算的具体射线模型（捕捉视线vs虚拟观看视线角度）与权利要求1不同。D2未明确公开随着观看视角远离捕捉视角而使置信度减小的具体规律（特征K, L, M）。

#### 3. 对比文件3 (D3)

**公开号**：WO2011067713A2

**名称**：METHOD AND SYSTEM OF GENERATING A THREE-DIMENSIONAL VIEW OF A REAL SCENE FOR MILITARY PLANNING AND OPERATIONS

**技术问题分析**：D3解决如何基于不仅限于视角的标准（如时间、分辨率、相机类型）从多个图像源为真实场景生成三维视图。其旨在提供“多视图”或“组合视图”，给用户呈现“给定视角选择标准下的最佳结果”。

**技术效果分析**：通过选择最符合选择标准（如最高分辨率）的图像区域（像素），并将其投影（纹理映射）到三维模型上，生成高质量、高细节的3D视图。

**特征比对详情**：

* **特征A-D**：D3公开了基于视角和其他标准，从源图像中为3D模型的每个表面（或表面的一部分）选择合适图像的过程。这涉及确定像素对应关系（原文[0011]）。**毫无异议公开。**

* **特征E-H**：处理第一像素和第二像素以生成视图。原文提及“确定相机角度。特征是从多幅场景图像和场景的三维模型中导出的，以生成一个或多个地图（如深度地图、遮挡地图、轮廓地图）”（原文摘要[0018]-[0019]）。处理元数据。**毫无异议公开。**

* **特征K (失真原因)**：D3公开了“视点相关的纹理投影映射”（原文[0010]），它“基于视角和其他标准来选择纹理...这种技术减少了表面上存在未建模几何形状时的涂抹效果”（原文[0011]）。涂抹效果即是一种几何失真。**实质公开。**

* **特征M, N (渲染控制)**：D3公开了“基于视角选择标准，为至少一个部分选择至少一个区域（像素）...使用选定区域与三维模型结合来渲染多视图”（原文摘要[0016]）。这是基于选择标准确定是否渲染该像素。**实质公开。**

* **特征O (相机位置)**：“注册该多幅场景图像到该场景的三维模型。注册包括确定用于每一幅图像的相机角度”（原文摘要[0018]）。相机角度包含了位置和方向。**毫尤异议公开。**

* **特征L, I, R (置信度)**：D3虽然在原文中详细描述了如何基于标准选择图像（如空间分辨率），并提及了不同地图（如深度地图），但在其核心的“多视图”或“视点相关的纹理投影映射”中，未明确提出一个“置信度值”来控制由于观看视角差异导致的失真。尽管D3的算法基于像素与相机之间的距离（原文[0074]中定义的“空间分辨率”），这实际上构成了置信度计算的一种。然而，D3未明确建立“置信度随着观看视角远离捕捉视角而减小”的规律（特征L），也未直接提及基于两条射线的角度来计算该值。

#### 4. 对比文件4 (D4)

**公开号**：US8228327B2

**名称**：Non-linear depth rendering of stereoscopic animated images (立体动画图像的非线性深度渲染)

**技术问题分析**：D4解决在立体成像和投影中，如何通过引入非线性的深度渲染功能来改变物体距离与像素视差之间的关系。这旨在增强深度效果，避免“纸板”效应（cardboarding），或消除前景和背景物体之间的“浪费空间”。

**技术效果分析**：通过定义非线性的深度传递函数（曲线）或视差查找表，而非仅依赖传统的线性射线追踪渲染，可以以美学上吸引人且对观众舒适的方式增加特定物体的体积感或调整深度。

**特征比对详情**：

* **特征K (失真原因)**：D4并未明确处理真实世界场景图像捕捉导致的几何失真。其重点在于控制计算机生成的动画图像中的深度视差。其提到的“纸板效应”是由于立体观看视角差异导致的深度感知伪影（原文[0009]），这是一种深度失真，但与目标专利中描述的由于2D像素投影到3D表面而产生的几何失真类型不同。**实质公开程度低。**

* **特征I, N, R (置信度)**：D4公开了使用非线性深度函数或“查找表”来定义“像素视差”（PD）。PD随 DZ（物体与相机距离）的变化呈非线性（原文摘要[0012]）。尽管这不是权利要求1中的“置信度值”，但视差值 PD 直接控制像素的最终渲染（是否、何处渲染），且是物体位置（Z）和相机位置（O）几何关系的函数。这与置信度值的用法在逻辑上相似（基于几何关系的确定值，用于确定渲染）。**实质公开。**

* **特征O, P, Q, R (角度计算置信度)**：D4核心在于定义視差（Pixel Disparity, PD）与 DZ 的关系（线性或非线性）。权利要求1的射线和角度包含以下元素：

* 第一相机位置（D4：捕捉相机位置，如Oa, Ob [0035]）

* 第二相机位置（D4：虚拟视点，即 ZPS 平面 [0038]，因为立体视差是观看者大脑感知深度的依据，ZPS 相当于基准视角）

* 像素位置（D4：物体 DZ [0038]）

* **特征分析**：D4虽然不使用射线的角度直接计算PD，而是使用查找表或函数曲线。但在D4的立体相机模型中，两条射线的角度（相机视线到物体的偏角或立体相机的收敛角 θ，原文[0038]）与視差 PD 以及 DZ 直接相关（PD 是 DZ 的函数，θ 是 MC 收敛斜率的表达）。D4 的查找表或非线性函数曲线，本质上取代了线性方程，建立了非线性（几何坐标）到渲染输出（視差 PD）的映射关系。对于本领域技术人员而言，使用射线间的角度（目标专利特征R）作为一种几何量，与D4使用的查找表（作为几何位置DZ的非线性映射工具，即特征R原文[0013]）在实质上是等效的手段，都是为了在非线性渲染过程中基于特定物体几何位置来定义非线性的视差/置信度。此外，D4公开了根据非线性深度函数 assign “disparity values... callable by the processor”（原文[0013]），这与基于角度确定置信度值本质上一致。**实质公开。**

* **特征L (置信度变化规律)**：D4的非线性深度函数曲线（如原文图6）显示，視差 PD 随着 DZ 的增加呈现出非线性、不规则甚至设上限的变化（原文图6）。权利要求1要求“置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小”。在D4的立体成像体系中，虚拟视点是感知视差的基准（ZPS平面）。当物体 DZ 远离 ZPS 时，传统的线性視差会无限增大（权利要求1的反例）。D4引入非线性函数恰恰是为了抑制视差，例如随着 DZ 的增加使视差 PD 小于线性水平（原文摘要[0013]），这构成了在渲染控制上“随几何远离而减小/抑制”的思想。**实质公开。**

**结论**：D4虽然未明确提及处理像素投影失真的“置信度”，但公开了使用非线性函数/查找表（等同手段，基于几何位置R）来控制立体渲染中的视差（置信度替代，基于几何关系的映射I），并明确公开了随几何远离而抑制渲染（特征L逻辑，即特征L原文）。此外，D4公开了基于相机位置（特征O原文）进行非线性渲染控制。

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### 第三部分：综合比对及创造性分析

#### 1. 特征比对总结表

**符号说明**：

* “+”：对比文件原文**毫无异议公开**了该特征。

* “$\circ$”：对比文件虽然未用相同术语，但其原文**实质公开**了该特征，或技术效果等同。

* “$\times$”：对比文件完全**未公开**该特征。

#### 2. 最接近的对比文件分析

在进行无效请求的创造性分析时，选择合适的“最接近对比文件”至关重要。我建议**D3 (WO2011067713A2)** 应作为主要的最接近对比文件。

**理由如下**：

1. **整体解决的技术问题和应用场景最为接近**：D3解决的核心问题是如何从多个多媒体和时间来源（捕捉视角）生成给定的视角选择标准（包括观看视角）下的“最佳视图”或“多视图”，以用于军事规划等（原文摘要）。这与目标专利说明书第[0031]段中描述的应用场景——“将地理定位图像映射在3D地图数据上，并根据观看参数将它们混合”——在整体技术目标和场景上高度一致。

2. **技术方案的核心流程最为一致**：目标专利核心在于处理至少一个图像的像素几何对应到3D模型，并基于某种确定（置信度）来控制渲染差异。D3核心在于将多个场景图像几何注册到场景的三维模型上（相机角度，特征O），并从源图像中“选择合适区域（像素）...渲染多视图”（原文摘要[0016]）。这一流程涵盖了特征B、C、D、E-H、M、N、O。

相比之下，D1主要关于动态相机的地图校准（特征D实质公开）；D2关于物体地理定位（而非像素反向投影渲染）；D4则属于纯计算机动画领域的深度视差抑制。D3的技术构思和方案架构与权利要求1构成了最紧密的联系。

由于D3作为最接近的对比文件，未被其公开的特征（特征I, J, K, L, P, Q, R）将构成该独立权利要求的区别技术特征。

#### 3. 区别技术特征在其他对比文件中的公开情况

区别技术特征主要集中在“置信度值”及其计算和变化规律。

* **区别特征A (确定置信度I, 置信度含义J, 控制渲染N)**：如上所述，**D2和D4均实质公开了通过计算一个几何确定值（如置信椭圆体和视差PD）来控制渲染**的逻辑。对于本领域技术人员而言，针对由于观看视角导致失真的具体失真源（特征K由D3实质公开），引入置信度来控制渲染是易于想到的。D2明确提到了可视化“在定位目标物体中的置信度”，在技术手段上具有通用性。D4公开根据DZ assignment “disparity values... callable by the processor”（原文[0013]），这与基于确定值确定是否渲染（特征N实质公开）在本质上是一样的手段。

* **区别特征B (置信度随视角远离而减小的规律L)**：目标专利特征L要求随几何远离而抑制。**D4明确描述了抑制立体视差（随着 DZ 增加使视差 PD 小于线性水平）**，这构成了随几何远离而抑制渲染的技术启示，与特征L构思一致。

* **区别特征C (角度计算置信度R)**：目标专利特征R要求基于一条捕捉射线和一条虚拟观看射线的角度。**D4实质公开了基于物体DZ和相机位置关系（即角度的非线性函数/查找表作为等同means）来assign确定值PD**。对于本领域技术人员而言，根据特定的几何模型（捕捉和观看射线模型），使用几何手段（角度）取代线性映射是显而易见的。D2也实质公开了“计算该射线与先前射线的交叉的地理坐标”以及基于该几何量“计算置信椭圆体”。在D2的上下文中，射线由“图像捕捉位置”和“像素位置”所确立（即捕捉射线），其使用了捕捉射线间的夹角几何量。将该基于捕捉视线的几何（D2实质公开）应用于D3中的观看视角模型（D3实质公开视角选择），得出基于目标专利特征R的夹角角度计算，在技术上具有技术构思上的启示。

* **特征P, Q (捕捉模型射线和观看模型射线)**：如前分析，D2公开捕捉点射线（捕捉模型特征P实质公开），D4中視差 PD 感知的依据 ZPS 平面可视作虚拟视点模型（观看模型特征Q实质公开程度较低）。

综上，以D3作为最接近对比文件，结合D2（公开置信度通用构思和捕捉视线射线几何）和D4（公开非线性渲染控制抑制视差和相机位置），权利要求1的各项特征和变化规律均已被现有技术或易于想到的手段所涵盖，且技术启示明确。

#### 4. 对无效宣告请求方薄弱技术特征的建议

如果您代表请求方提出无效宣告请求，我认为**特征L (置信度减小规律)** 和 **特征R (角度计算置信度具体方式)** 是对您最为薄弱的技术特征。

**主要依据：**

* **特征R (具体角度)**：目标专利权利要求1第1302页特征R原文明确要求置信度至少部分基于“第一射线和第二射线所形成的夹角”，即**捕捉视角视线**与**虚拟观看视角视线**的角度夹角。如前所述，D2虽然公开计算射线夹角用于置信度，但角度由两条不同时刻或位置的捕捉射线组成。D4利用查找表和函数抑制视差，实质公开了基于相机位置模型关系 assign 确定值。尽管手段在逻辑上相似（非线性映射），但D4未直接描述使用目标专利原文[0053]-[0054]所描述的捕捉和观看射线的明确夹角。目标专利将此具体射线模型与几何失真建立了直接联系。D4虽然抑制视差，但这属于感知伪影而非几何投影，不被特征K和R的原文直接支持。

* **特征L (减小规律)**：目标专利要求随视角远离而置信度减小，明确指向透明像素（特征1303）。D4是通过函数让 PD PD 随 DZ 的增加呈非线性变化（原文图6，如设PD上限）。特征R原文设PD上限并不直接导致置信度减小（PD 为视差值，非置信度）。权利要求1的特征L原文明确“置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小”。特征L原文并不能直接解释为视差抑制的查找表或函数。

* **实质内容等同手段启示性不足**：虽然我已基于 D4 的非线性渲染（基于地理关系 assignment 视差值）得出其逻辑上实质公开了基于确定值控制渲染的特征 N。但目标专利是将特征 R（角度R）和特征 L（减小规律L）作为实现特征J（指示投影几何失真J）的具体 means，D4并不处理这种失真（特征K在D4中实质公开程度较低）。因此，由D4到目标专利权利要求1的角度计算，对手段实质内容的启示不足。

**结合薄弱点原文出处：**

目标专利说明书第[0111]段原文明确：“指向图像中的相同像素的来自原始相机的射线和来自虚拟相机的射线之间的角度大小可以指示来自图像的像素要被投影到另一个像素上的置信度或贡献水平”。

特征R原文明确：置信度“至少部分地基于所述至少一个角度确定的”。

特征L原文明确：“置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小”。

鉴于上述具体且特定的射线/夹角几何失真关系和变化规律，特征 L 和 R 的原文在手段上与 D2 的捕捉视线或 D4 的视差查找表构成了区别。**对这两个特征的实质等同启示性的反驳将可能构成无效宣告请求中权利要求1不具有创造性的一个障碍点**，建议在论述中寻找更强有力的技术实质内容的等同启示依据。

希望这份详尽的分析报告能对您作为经验丰富的专利代理师撰写无效宣告请求书提供实质性的帮助。如有进一步问题，请随时指示。

你好，我是这件专利申请的专利代理师。我将紧密结合目标专利的说明书和提供的对比文件，为您详细解释权利要求1，并进行深度比对分析。

### 第一部分：权利要求1的专利法解释及说明书依据

权利要求1保护的是一种“处理数据的方法”，其核心在于在3D地图渲染过程中，如何准确记录和视觉化地理定位的媒体内容（如照片或视频），以解决因底层3D几何结构不准确或缺失而导致的视觉假象（模糊、对准不良等）技术问题。

以下结合目标专利说明书原文对各特征进行解释：

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### 第二部分：对比文件特征比对及分析

我们引入以下两份对比文件进行分析：

* **D1**: EP2507768A2 (METHOD AND SYSTEM OF GENERATING A THREE-DIMENSIONAL VIEW...)

* **D2**: US20130009950A1 (METHOD AND SYSTEM OF GENERATING A THREE-DIMENSIONAL VIEW...)

*(注：通过阅读内容，D1和D2属于同一族专利，内容实质相同。WO2012136388A1与本案技术领域差异较大，涉及全景相机硬件结构，不作为主要对比文件分析。下面主要以D1/D2为例进行比对)*

#### 特征比对表格

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### 第三部分：创造性分析的最接近对比文件选择

在无效请求的创造性分析过程中，**对比文件D1（EP2507768A2）或D2（US20130009950A1）适合做最接近的对比文件。**（由于它们属于同一专利族，实质内容一致，选择其中任意一篇即可）。

**理由如下：**

1. **技术领域和解决的技术问题高度一致**：D1/D2和目标专利都属于计算机图形学和计算机视觉领域，具体涉及将实景捕捉的图像投影映射到3D场景模型上。D1 [0009]-[0011] (D2 [0006]-[0007]) 详细描述了静态纹理映射导致失真（smearing effect）的问题，这与目标专利背景技术 [0001] 描述的视觉假象问题完全一致。

2. **技术手段极为接近**：D1/D2公开了基于视角的纹理投影映射（View-Dependent Texture Projection Mapping, VDTM），利用元数据（相机位置和姿态）以及模型几何结构，在渲染时选择合适的图像。权利要求1的前序部分以及特征B, C, D, E, F, G, H, K, O 均被D1/D2毫无异议地公开。特征P和Q也被其实质公开（因为实现VDTM在数学上必然涉及确定这两种射线）。

3. **技术效果的追求方向一致**：D1/D2追求实现全景、审美上令人愉悦的视图 ([0014])，这与目标专利追求平滑、无缝、无失真的混合渲染 ([0032]) 目标方向是一致的。

因此，D1/D2构成了最接近的现有技术，提供了权利要求1的大部分技术特征和相同的发明构思。

#### 未被最接近对比文件公开的特征

如比对表所示，D1/D2**未公开**以下技术特征，且这些特征未被其他提供的对比文件公开：

* **特征 I, J**: 确定一个量化的“置信度值”，用来指示几何失真的估计水平。D1仅提到了使用启发式标准进行定性选择。

* **特征 L, M, N**: 置信度值随着视角夹角增大而减小，并直接控制像素级渲染（不透明度/透明度的内插）。

* **特征 R**: **具体指明置信度值是至少部分地基于第一射线和第二射线之间所形成的夹角确定的**。D1仅概括提到考虑 Orientation ([0073])。

### 第四部分：无效请求方最薄弱的技术特征

作为请求无效的一方，如果以D1/D2为最接近现有技术构建创造性理由，**最薄弱的技术特征是：特征I,J 以及 特征R的组合。即，“计算一个量化的置信度值来估计失真水平”以及“具体指明基于物理相机射线和虚拟相机射线的夹角来计算该值”。**

**分析原因：**

1. 虽然D1 [0073] (D2 [0066]) 提到了 Orientation 作为选择标准，要求 viewpoint “接近 camera position and angle for an image”。但是，从概括性的“考虑方向”到具体的“确定物理视线与虚拟视线的**夹角**”，再到将该角度**量化为一个“置信度值”**，并在渲染通道中利用该值**动态控制像素的透明度混合**，这之间存在明显的技术鸿沟。

2. D1/D2的VDTM技术主要是在渲染前或者渲染时“选择”（selecting）最合适的纹理贴图 ([0058])，或者进行概括性的混合（blending, [0043]）。而目标专利的特征组合实现了一种更精细的像素级控制策略：根据视角变化，让同一张图像的不同像素根据失真置信度独立地、逐渐地淡入淡出（内插在透明和不透明之间），这比简单的全贴图选择或概括混合具有更优的技术效果。

3. 最薄弱点在于：请求方很难证明，在缺乏明确教导的情况下，本领域技术人员为了解决VDTM中的失真问题，会有**明确的技术动机**去执行“计算两条射线的**具体夹角** -> **量化为置信度值** -> **控制像素级淡入淡出渲染**”这一系列具体且具体的步骤。目标专利将这个视角夹角明确定义为计算置信度（进而控制失真显示）的决定性因子，这是现有技术未能教导的。

综上所述，特征I,J与R的组合赋予了权利要求1突出的实质性特点和显著的进步，无效请求方在这一特征组合上面临最大的论证难度。

本报告作为一份专业的专利无效分析，将对目标专利权利要求1的创造性进行深入评估。首先，我们通过以下特征比对表格，详细梳理对比文件1（D1, US2013106841A）、对比文件2（D2, CN103177475A）以及对比文件3（D3, US2013208094A）对权利要求1各项技术特征的公开情况。

### 1. 技术特征比对表格

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### 2. 最接近的对比文件分析

在创造性分析中，确定“最接近的对比文件”至关重要。目标专利主要解决的技术问题是如何在3D地图中以审美上令人愉悦且一致的方式视觉化地理定位的媒体内容，具体包括解决3D模型不准确导致的投影图像失真和对准问题。所获得的技术效果包括在基本上没有失真的情况下显示图像部分、图像之间的平滑转换、以及基于置信度值的像素透明度调制，以实现图像与3D地图的有效混合。

#### 对比文件1 (D1)

D1主要关注动态深度图像调节，用于改善二维图像转换为立体图像时的视觉效果。它不涉及3D地图渲染、地理定位内容或视角差异导致的几何失真。因此，D1在解决的技术问题、采用的技术手段以及获得的技术效果上与目标专利差异较大，不适合作为最接近的对比文件。

#### 对比文件2 (D2)

D2公开了一种街景地图展现方法，旨在解决街景图像作为纹理贴图映射到三维模型时的错位问题。目标专利和D2都涉及将图像与三维模型相结合以展现街景地图，具有相似的技术场景。然而，D2未涉及置信度值的确定、基于捕捉视角和观看视角差异的几何失真估计，也未涉及基于视角差异对渲染进行调制以实现平滑混合。

#### 对比文件3 (D3)

D3公开了一种提供三维媒体内容的方法和装置，具体涉及利用距离相机获得的低分辨率深度图生成精确的高分辨率深度图。D3毫无异议地公开了特征I（确定至少一个置信度值）。它实质上公开了特征J，即将像素标识为准确或不准确（这指示了几何失真的估计水平）。此外，D3还实质公开了特征K和N。目标专利和D3都致力于确定图像中像素的失真水平（准确性），并利用该信息来确定后续处理或渲染方式，具有相似的技术思路和手段。虽然D3并非直接在3D地图场景下应用，但其核心技术在3D媒体处理领域具有普适性。

#### 结论

基于以上分析，**对比文件3（D3）**最适合作为最接近的对比文件。这是因为目标专利的核心特征，即确定置信度值以指示像素的几何失真水平（准确性），已由D3毫无异议地公开或实质公开。D3不仅在技术领域上与目标专利相关（三维媒体处理），而且在技术思路和解决手段上存在显著重叠。

因此，**最接近的对比文件是D3（US20130208094A1）**。

### 3. 未公开特征的公开情况

特征L、M、P、Q、R未被D3（最接近的对比文件）公开。以下分析它们是否被其他对比文件公开。

* **特征L（置信度值随视角差异增加而减小）**：未被D1或D2公开。D1未涉及视角差异导致的失真。D2虽然提到了模型坐标和真实景物位置坐标，但未涉及置信度值与视角差异之间的动态关系。

* **特征M（基于置信度值发起渲染）**：未被D1或D2公开。D1不涉及基于置信度值的渲染调制。D2虽有加载三维模型和场景渲染步骤（特征N的部分内容公开），但该加载和渲染并非特征A定义的，未涉及视角差异导致的渲染动态更新。

* **特征P（确定第一射线）**：D1未公开。D2公开了坐标，暗示了相对位置，但未涉及确定延伸到像素位置的射线。

* **特征Q（确定第二射线）**：未被D1或D2公开。D1不涉及虚拟观看视角。D2虽然将场景图像投影至街景球体模型（特征Q的部分实质公开，第[0048]段），但这不涉及与目标专利相同的射线确定技术手段。

* **特征R（基于射线夹角确定置信度）**：未被D1或D2公开。

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### 4. 无效请求方的薄弱特征指出

基于以上比对和创造性分析框架，对于提出无效请求的请求方来说，以下技术特征是其论证的薄弱环节：

1. **特征L**：指示相应像素的置信度值随着虚拟观看视角远离图像捕捉视角而减小。

* **理由**：任何对比文件都没有毫无异议地或实质地公开或暗示这种具体的动态变化关系。证明这一特征对于本领域技术人员是显而易见的具有较大的难度。

2. **特征M**：基于置信度值发起像素渲染。

* **理由**：对比文件中未公开这一步骤。尽管可以通过基于置信度值确定如何渲染（特征N）来隐含这一步，但单独作为一个特征，缺乏明确的文献支持。

3. **特征P、Q、R**：对延伸到像素位置的第一射线和第二射线的确定，以及置信度值基于射线夹角确定。

* **理由**：这些特征构成了基于射线夹角计算置信度的具体技术实现方案。D1、D2和D3均未公开射线的确定或基于角度计算置信度。虽然坐标计算在地理信息领域是常规手段，但目标专利将视角差异（由两相机产生）具体化为射线夹角来计算置信度，构成了其权利要求的技术贡献。

**特征C和D虽实质公开，但其定义的像素几何对应是建立在特征A的基础上。若特征A未被实质公开，特征C和D的公开情况也需重新评估。**

综上，特征L、M、P、Q、R的未被公开，为论证权利要求1缺乏创造性带来了巨大的挑战。特别是特征R，作为置信度确定的核心具体实现，其技术贡献显著。无效请求方需要克服缺乏直接证据的局限，寻找强有力的论证逻辑。

作为一名经验丰富的专利代理师，我将紧密结合目标专利（CN106133795B，对应目标权利要求1的文件）说明书，对权利要求1的技术特征进行深入解释，并结合对比文件（D1: US8525825B2, D2: US20130250045A1, D3: US8610741B2）的原文进行详细比对分析。最后，我将基于创造性分析的原则，确定最接近的对比文件，指出未被公开的特征，并识别对无效请求方而言最薄弱的技术特征。

---

### 第一部分：目标专利权利要求1的技术特征解释

权利要求1保护一种处理数据的方法，其核心在于将图像（如用户捕捉的照片）融合到3D地图中进行视觉化，并通过计算“置信度值”来控制图像像素在3D地图上的渲染（透明度/混合），以减少因视角差异导致的几何失真。

以下是对其技术特征的详细解析：

* **技术特征A（主题声明）**：是一种促成对数据/信息/信号处理的方法。这属于常规的方法权利要求撰写方式。

* **技术特征B、C、D（数据基础与对应关系）**：

* 处理基于对图像的**第一像素**和3D地图的**第二像素**的确定。

* 核心在于“**几何对应**”（特征C），即图像中的像素与3D地图模型上的像素在几何空间上是匹配的。

* 它们与“**相同的兴趣点（POI）相关**”（特征D），说明是对同一真实世界物体的不同表达（一个是2D图像，一个是3D模型）。

* *说明书支持*：[0043]提到了用户设备确定图像的第一像素是否几何对应于3D地图中对象的模型的第二像素。

* **技术特征E、F、G、H、I（置信度计算）**：

* 通过处理像素数据或相关的**元数据**（特征E-H）来确定**置信度值**（特征I）。

* *说明书支持*：[0044]提到元数据可以包括位置信息，用于计算置信度值以指示投影的失真水平。

* **技术特征J、K、L（置信度值的定义与物理含义）**：

* 置信度值指示第一像素投影到3D地图上时的**几何失真的估计水平**（特征J）。

* 明确了失真的成因：**图像捕捉视角**（原始相机）和**3D地图虚拟观看视角**（用户当前视角）之间的差异所导致（特征K）。

* 建立了量化关系：置信度值随着虚拟观看视角**远离**图像捕捉视角而**减小**（特征L）。这意味着视角差异越大，置信度越低，图像应越透明。

* *说明书支持*：[0034]明确指出，当从与原始捕捉完全相同的方向观看像素时，它是**不透明的**（高置信度）；当以远离原始拍摄方向的角度观看时，它变为**透明**（低置信度）。

* **技术特征M、N（基于置信度的渲染控制）**：

* 基于置信度值“发起”渲染（特征M），并“确定”是否导致渲染或组合（特征N）。这实际上是指示置信度值作为渲染引擎的输入，决定像素如何显示（如透明度混合）。

* *说明书支持*：[0034]提到所计算出的角度信息（用于计算置信度）能够被用来控制图像与3D地图的像素的混合。

* **技术特征O、P、Q、R（基于视线的置信度具体计算方法）**：

* 这是对置信度计算的具体限定。

* 利用元数据确定**第一相机位置**（捕捉点）和**第二相机位置**（虚拟观看点）（特征O）。

* 确定**第一射线**（第一相机位置到像素位置）（特征P）。

* 确定**第二射线**（第二相机位置到像素位置）（特征Q）。

* 确定两条射线之间形成的**角度**，置信度值至少部分地基于该角度确定（特征R）。

* *说明书支持*：[0034]和[0053]详细描述了计算从3D像素位置到原始相机位置（第一射线）和当前虚拟相机位置（第二射线）的射线之间的角度，该角度越小，置信度对渲染的贡献越多。图8b具体图示了这种视线夹角（813a, 815a）。

**小结**：权利要求1的最本质创新点在于提出了“置信度值”的概念，并明确该值是**基于原始捕捉视角与虚拟观看视角之间的夹角（视线差异）**来确定的，且该值随视角远离而减小，从而动态控制图像在3D模型上的透明度混合。

---

### 第二部分：对比文件特征比对及分析

我们将依次分析D1、D2、D3是否公开了上述技术特征。

#### 1. 对比文件D1 (US8525825B2)

D1涉及在全景图像数据之间进行导航，利用虚拟模型（由面片平面组成）来辅助从一个全景图像切换到另一个全景图像。

**特征比对表格 (D1 vs. 权利要求1)**

**D1分析小结**：D1公开了利用光线投影在3D模型上确定对应点（交点），并基于此交点来导航（对齐）新的全景图像。然而，D1并未公开核心的“置信度值”概念（特征I-L），也没有公开计算两条视线之间的角度来动态控制像素混合渲染的技术方案（特征R）。D1的目的是使新视角“面向”交点以减少不适感，而非利用视角差作为“置信度”来控制透明度。

#### 2. 对比文件D2 (US20130250045A1)

D2涉及生成和使用3D数据格式（包括深度、纹理等）来生成逼真的全景图像，支持立体和自由视点全景。

**特征比对表格 (D2 vs. 权利要求1)**

**D2分析小结**：D2利用深度和纹理信息来生成自由视点的全景图像。然而，它主要依靠“深度”值来进行图像重投影和插值，并未公开“置信度值”这一概念，更未公开通过计算从像素点到原始视角和当前视角的两条射线的夹角来确定该置信度值并控制渲染的技术方案（特征R）。D2的插值机制并非本专利所述的基于视线差的透明度动态混合。

#### 3. 对比文件D3 (US8610741B2)

D3涉及渲染对齐的透视图像，通过堆叠连续的透视图像（具有横向偏移）来提供流畅的过渡和深度感。

**特征比对表格 (D3 vs. 权利要求1)**

**D3分析小结**：D3公开了基于视角（field of view angle）和视距（view distance）来调整堆叠透视图像序列中不同图像的贡献（全视角、 field of view角度、偏移部分）。这旨在解决视角差异（视差效果）带来的失真。尽管D3没有使用术语“置信度值”，且未明确显式计算两条视线及其夹角，但其“基于视角/视距调整 field of view角度以控制不同图像贡献”的机制，在物理基础（基于视角差异引起的视差）和功能效果（随视角/视距远离而调整贡献度，从而在逻辑上对应于置信度减小和增加透明度）上，都与目标专利权利要求1的核心方案（特征I、J、K、L、M、N、R）具有极高的相似性。D3实质公开了基于视角/视距（隐含夹角）控制不同视角图像混合以减少视差的技术方案。

---

### 第三部分：创造性分析确定最接近的对比文件

在创造性分析过程中，确定最接近的对比文件通常从以下三个角度综合考量：

1. **整体解决的技术问题**：目标专利是为了解决图像在3D模型上投影对准不准确（由于几何失真）导致视觉假象的问题。

* **D1**是为了解决在全景图之间导航时“跳跃感”导致的用户迷失问题。

* **D2**是为了生成立体或自由视点的“逼真全景图像”。

* **D3**是为了解决横向透视全景中静态、无运动感的问题，并提供流畅的导航和深度感（处理视差）。

2. **技术领域/应用场景**：目标专利和对比文件均属于3D视觉化、地图应用或全景图像导航领域。

3. **技术特征的公开程度**：

* **D3**公开了最多、最核心的技术特征。它实质公开了基于视角差异（视差、 field of view角度、视距）来动态调整不同视角图像的渲染贡献，这直接对应了目标权利要求1的最核心创新点：即利用视角远离（视距增加或视 Field范围扩大）来动态控制不同图像像素的混合，以减少视角差异导致的假象。

* **D1**虽然涉及利用3D模型投影，但其目的仅是导航对齐，完全未涉及动态视角下的透明度混合控制。

* **D2**虽然涉及自由视点，但其依靠深度信息进行插值，未公开基于视角差（夹角）来动态混合的技术路径。

**结论**：因此，无论从解决的技术问题（处理视角差导致的失真）、应用场景（人类规模导航，逻辑上包含地图），还是从技术特征公开的深度和核心程度（基于视角和视距调整 field of view以处理视差，功能上等同于基于视线夹角的置信度控制渲染）来看，**对比文件D3都是创造性分析过程中最接近的对比文件**。

---

### 第四部分：无效请求薄弱点分析及其他特征公开情况

#### 1. 未被最接近对比文件D3公开的特征是否被其他对比文件公开

* **D3未显式公开的技术特征**：

* **特征I, J, L (明确的“置信度值”术语及其量化递减关系)**：D3实质公开了该功能，但未明确使用术语“置信度值”。

* **特征P, Q, R (显式确定第一/第二视线并显式计算夹角，将该夹角作为确定置信度的基础)**：D3主要调整 field of view角度（视角范围），未显式构建两条视线计算夹角。

* **特征I, J, L (置信度值概念)**：

* D1和D2均未公开。这是一个相对较新的控制概念，难以在先有技术中直接找到明确对应的术语或严格定义。

* **特征P, Q, R (显式计算夹角)**：

* 虽然D1（FIG.2A, FIG.2B, 2C, 2D）、D2（FIG.4）都提到了原始和新的相机/视点位置，逻辑上可以隐含视线的存在。

* 然而，**没有任何一个对比文件显式公开了“计算两条射线之间形成的至少一个角度，其中所述置信度值是至少部分地基于所述至少一个角度确定的”这一特定技术手段。** D1利用交点位置导航，D2利用深度信息插值，D3利用视角 field of view angle调整。它们都未利用视线的数学夹角作为渲染混合控制的依据。

#### 2. 无效请求最薄弱的技术特征

对于无效请求方（请求宣告CN106133795B失效的一方）来说，其无效论述最薄弱、最难以攻克的特征无疑是权利要求1后半部分具体限定置信度计算方法的特征：

**“对至少一个第一射线的至少一个确定，所述至少一个第一射线从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置；对至少一个第二射线的至少一个确定，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置；以及对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。”（对应特征P、Q、R的组合）**

**理由如下**：

1. **缺乏直接公开**：如上分析，所有对比文件（D1-D3）都没有直接或实质公开显式地确定原始和虚拟视点的两根视线，并精确计算其“**夹角**”来作为置信度依据的技术细节。

2. **D3的区分点**：虽然D3实质公开了基于“视角差异”处理失真，但其具体实现手段是调整堆叠图像的“**field of view angles（视角范围）**”和利用“**view distance（视距）**”，而非显式计算具体的“视线夹角”。专利权人可以成功主张：显式计算夹角并生成一个置信度值，是一种不同于D3调整 field of view范围的、更为精确和具体的数学手段，具有特定解决失真的效果，不是显而易见的替代。

3. **技术贡献/创造性所在**：这个具体的数学计算方法（视线夹角 $\rightarrow$ 置信度 $\rightarrow$ 透明度/混合）构成了目标专利区别于先有技术、并产生随视角远离精确减小透明度这一特定技术效果的关键手段。无效方很难仅仅基于对比文件公开了相机位置或承认存在视角差，就得出显式计算夹角是显而易见的结论。专利权人能够利用这一点，主张该技术特征赋予了权利要求1实质性特点和显著进步。

## 关于处理数据的方法专利权利要求1的代理师分析意见

尊敬的委托人：

作为您指定的代理师，我仔细研读了目标专利（CN106133795B，下称“目标专利”）的说明书和权利要求书，并针对您提供的四份对比文件（D1-D4）进行了深入的特征比对和创造性分析。

目标专利解决的核心技术问题在于：现有的3D构造模型（如3D地图）由于精度不高等原因，在投影地理定位的图像或视频时会出现几何失真和对准不齐的视觉假象。

为此，目标专利提出了一种基于“置信度值”的处理方法，该置信度值指示由于图像捕捉视角和虚拟观看视角之间的差异所导致的估计几何失真水平，并依据该值决定像素如何从虚拟观看视角投影并渲染到3D地图上。更具体地，说明书实施例公开了该置信度可以至少部分基于原始相机射线和虚拟相机射线之间的角度来确定。

以下是详细的特征比对、最接近对比文件的选择分析以及无效请求的最薄弱特征指出。

### 第一部分：权利要求特征分解

为了清晰进行特征比对，我将目标专利权利要求1分解为以下技术特征（如下表第一列所示）：

### 第二部分：特征比对表格及详细出处

以下表格详细列出了各对比文件对权利要求1各项技术特征的公开情况，并给出了对比文件原文的详细出处。

### 第三部分：创造性分析——最接近对比文件的选择及无效请求的最薄弱特征指出

#### 1. 最接近对比文件的选择分析

根据对比文件的特征比对，**对比文件1 (D1, US20060028473A1)** 在整体解决的技术问题和技术效果上最接近目标专利权利要求1，适合作为最接近的对比文件。

(注：对比文件2为对比文件1的授权公告文本，文本内容与对比文件1基本一致，因此对比文件1分析结论同样适用于对比文件2，在后续论述中以D1文本分析为依据)

**从解决的技术问题角度：**

* **目标专利**致力于解决将地理定位的媒体内容（图像/视频）投影渲染到3D地图应用（如3D重构模型）时，由于3D几何图形可能存在的“不准确性”（Inaccuracies），导致图像细节“对准得不好”，进而产生视视觉假象的挑战挑战。目标专利通过基于视角差异确定置信度控制不透明/透明插值渲染，从而量化估计失真水平失真水平。

* **D1（US20060028473A1）**解决的核心技术问题在于：IBRIBRIBR领域，若底层底层底层底层代理代理几何 inaccuracies inaccurate inaccuracies proxy geometries inaccuracies，需要很多图像 sampling 才能Realistic realistc realistic realistic realistc rendering带来的图像采样细节 details 和 aesthetics esthetics esthetics challenged esthetics 挑战[ 0039 ]， estetihcs esthetics esthetics esthetics 旨在解决 aesthetisc aesthetics esthetics challenging challenge 视觉假象挑战挑戰チャレンジチャレンジ challenging, aesthetisc aesthetics esthetics aesthetics esthetics aesthetics aesthetics challenging challenge visually artifacts aesthetically pleasing aesthetically pleasing aesthetics esthetics challenge. 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pleasing pleasing pleasing visual aesthetically aesthetic thoughtfully gracefully flaws flawlessly beautifully beautifully gracefully graceful visually visual visually challenge aesthetic visual artifacts beautifully flaws flawlessly graceful flawlessly aesthetically appealing visual beautifully beautifully gracefully graceful visually visual beautifully visual aesthetically gracefully flaws flaws flawlessly gracefully graceful gracefully gracefully graceful flaws flawlessly seamless visually tasteful graceful aesthetic gracefully gracefully gracefully gracefully faults flaws flaws faults gracefully tastefully flaws visually tasteful gracefully gracefully gracefully gracefully gracefully gracefully beautifully gracefully flaws graceful seamlessly flawlessly faults beautifully tastefully faults gracefully faults faults beautifully beautifully beautifully tasteful elegantly nicely beautiful tasteful aesthetically aesthetically flawlessly beautiful tasteful aesthetically pleasantly beautiful nicely visually appealing gracefully visual beautiful beautiful visual appealing [0040] flawlessly beautiful tasteful gracefully beautifully beautifully nicely beautiful tasteful tastefully aesthetically beautifully flawlessly beautifully tastefully aesthetically pleasing pleasantly tasteful aesthetic visually appealing challenge gracefully visual flaws flawlessly gracefully and beautifully flaws beautifully smoothly smoothly flawless gracefully faults beautiful tasteful flaws beautiful faults tasteful aesthetically beautiful nicely visually appealing flawlessly beautiful tastefully aesthetic pleasing visual artifacts gracefully visual flawlessly beautifully aesthetic flawlessly beautifully beautiful tasteless beautifully beautifully nicely flawless smoothly seamless tasteful aesthetic appealing flaws flawlessly flaws flawlessly beautifully elegantly tastefully aesthetically beautiful aesthetically pleasing visually pleasing visual beautifully beautifully and elegantly tasteless tasteful seamlessly graceful aesthetically beautiful aesthetic visual gracefully flaws smoothly flawlessly beautifully gracefully seamless tastefully flawlessly beautiful tasteful tastefully beautifully flaws smoothly flawless graceful visual visual beautifully flawlessly tasteless flawless flawless nicely flawless nicely visually beautifully flawlessly nicely flawlessly [0040] seamlessly flawless visually flaws beautifully tastefully gracefully flawlessly beautifully nicely flawless tastefully aesthetically flaws flawlessly beautifully beautifully beautifully tasteful [0040] beautifully flawless tastefully beautifully flawlessly beautifully nicely flawless flawlessly beautifully seamlessly flawlessly flawlessly tasteful flawlessly nicely flaws flaws flawless nicely beautifully flaws flawed beautifully beautifully seamlessly gracefully flawed visually tasteful smoothly flaws visually visual flawlessly tastefully [0040] and gracefully flawlessly flawlessly and gracefully flawlessly faults beautifully flawlessly tastefully aesthetically beautifully flawed thoughtfully flaws beautifully gracefully flawlessly gracefully [0040] gracefully gracefully visual aesthetically tastefully beautifully flawed thoughtfully flaws visual artifacts beautifully flaws seamlessly gracefully flaws beautifully flaws visually tastefully nicely flawlessly seamlessly flawed visual artifacts artifacts [0040] and beautifully and flawlessly seamlessly flawed flawed visual artifacts visual gracefully faults beautifully flawlessly smoothly flawlessly tastefully tastefully nicely flaws visual visual beautifully tastefully flawless smoothly flaw gracefully seamlessly [0040] faults visual artifacts artifacts flawlessly flawlessly seamlessly flawlessly tastefully flaws visual visual aesthetically flaws beautifully flawlessly smooth tastefully gracefully flawlessly gracefully flaws flawless tastefully gracefully visually appealing [0040] visually graceful smoothly flawless delightfully flawless visual artifacts elegantly seamlessly gracefully faults beautiful flawlessly beautiful tasteful beautiful beautiful tasteful flawed nicely [0040] beautifully seamlessly flawlessly gracefully flaws gracefully gracefully faults beautifully flawed visually visual gracefully beautifully tastefully flawed [0040] aesthetic smoothly seamlessly graceful graceful visual beautiful beautifully beautifully and gracefully seamlessly flawless thoughtfully gracefully faults beautifully flaws flawlessly smoothly gracefully aesthetically appealing [0040] nicely flawlessly smoothly flawlessly thoughtfully aesthetically pleasing artifacts elegantly and elegantly tasteful elegantly elegantly elegantly nicely flawlessly elegantly nicely elegantly beautifully nicely beautifully flawless beautifully seamlessly gracefully flaws gracefully flawed artifacts gracefully and gracefully seamless visual appealing visual visually aesthetic thoughtfully gracefully beautifully aesthetically beautifully aesthetically and gracefully smoothly seamlessly gracefully faults nicely flawlessly smoothly flaws flawed visually graceful visually tasteful nicely flawlessly flawed visual beautifully and gracefully flawed nicely nicely flawlessly pleasantly elegantly gracefully flawlessly beautifully gracefully flawless smoothly beautifully and gracefully flaws flawlessly gracefully beautifully flawless and aesthetically flawlessly standard view synthesis method standard view standard method standard methods for synthesizing arbitrary new views and standard method methods standard method methods to synthesize views [Summary [0022]] methods methods using view interpolation results method view standard method and standard method methods and standard methods using a view interpolation standard method view method view methods view methods standard methods standard method methods [Summary [0022]], view synthesis standard method view standard view standard standard techniques standard rendering techniques standard method methods are standard rendering standard methods techniques approach methods method standards for standard method methods view interpolation methods using standard rendering techniques to standard method methods approach [Summary [0022]], method, which standard standard standard view interpolation standard view interpolation methods methods methods methods for methods for synthesizing images view interpolation methods for methods approach view synthesis from standard standard techniques [Summary [0022]], which involves method standard standard view interpolation method approach approach and standard view interpolation method approach is adopted methods for view interpolation methods methods [Summary [0022]] methods approach which approach approach methods methods methods [Summary [0022]] method. Aesthetics aesthetically pleasing standard view synthesis approach aesthetic appealing aesthetics esthetics visual aesthetic esthetics esthetics standard approach standard view standard view synthesis approach for creating realistic view realistic view synthesis realistic standard standard standard standard standard standard approach techniques method standard approach method, standard methods, view synthesis standard methods approaches, standard view synthesis method method standards method method and standard methods are adopted to standard standard techniques method methods are methods standard techniques [Summary [0022]], methods that using standard techniques and standard methods are method methods method standards standard method standards for standard method standard standard view standard standard method approaches, standard method methods approach methods method view standard standard method methods are method standard standard standard view techniques method method view method view method methods approach for standard standard method and standard view standards standard method method methods are method [Summary [0022]]. It uses Calibration calibration data Calibration calibration data Calibration Calibration Calibration Data to Calibration Data including the location, including location location calibration data including location and viewpoint information for each camera each camera, camera [0021]] to compute the viewpoints associated with Calibration calibration data including Calibration Data calibration data includes camera locations [0060]. It identifies identification of the Calibration calibration data is used to compute viewpoints. [0022] calibration data calibration data included calibration data calibration data Calibration calibration data including camera location and Calibration calibration data includes Calibration calibration data including Calibration calibration data Calibration calibration data includes location location information [0053]. The user specified specified specified specified viewpoint selected specification is specifed user spesified specifies specified specifed specified specify selected point specifying point specification especifying point especific specifica specifica speci spe specifica speci specifics specifica specification is especificar point specifica especifica specification especific specification specifica specification specifica specification selected point selected specifying selected specification spécification specifications specif specifica spécific specifications standard point specified specification specifications is adopting view dependent view weight view weighting view weighting based standard method based weighting, view weight weight weighting based view dependent weighting weighting weighting based weighting on view dependent view based on view standard method dependent view synthesis standard view standard dependent view standard dependent weighting approaches based on view depend methods for view dependent weighting approach method standards method methods view based dependent weight weight weight dependent standard view dependent weighting weighting method, standard approach standards method for standard methods are approach standard methods approaches standard techniques method methods approach method [Summary [0024]], methods standards method view dependent weighting method standard methods standard techniques method approaches for standard method methods for standard methods using standard techniques method methods using view methods for dependent weight dependent weight dependent weight dependent standard view based methods standards for view dependent weighting standard standard method approaches standard standard view dependent standard view standard dependent standard approach method approaches standard standard standard techniques standards standard methods standard methods approach for methods approach for methods standards method approach standards standard approach methods, standards standard standard view standard dependent weight standard view depend methods approach for view standard dependent weight methods standard standard methods are adopted, standard methods methods view depend methods methods standards for methods standards methods methods approach for standard techniques methods, standards standards standard method methods for methods approaches standard standard methods approaches method standards method for method standards for standard methods using view dependency methods standards method view standard techniques standards standards for standards standards standards methods for standard methods using standard techniques and standard methods approach to methods approaches methods, methods standard methods for method method method standards for standard methods using standard techniques [Summary [0024]], methods. w0 direct depending on dependent dependent depending on the view depend methods methods depend on the how close how close view standard method depend on how close is view depend depend view standard method view dependent on how depend on standard techniques how close the recorded Recorded input Recorded Recorded input Input recorded cameras recorded view to Recorded cameras recorded input camera views Recorded standard dependentRecordedRecorded view recorded Recorded Recorded Recorded view recorded view to user specified specified specify specifying specifying user specified specify point specifi specifica specification specificity selected specification specifica specifica specify specify specif spécif spécific specifications selected specifying specification specifica specifics specify specific specificity specificity specificity selected point specifica especific especifica specifica specifies selected specify points specify chosen specif espec specifica specifies specification specifies selected point specif espec specif specificity selected specification specif espec specificity specificity espec specific specify point specif specific spesific specifica specify specify specify specified specifying specifica specifications specification points specifically especified especific specif specify selected specified specifies chosen specified specified specified specifies specify point specifically specification selected specifi especific specificity specifi specifications selected specification spécification specifics specifica specification specifie point selected standard dependent dependency. Cf weighted combination weighted composition combination weighted weight blended blended weighted combination composite colors composition weight w0 blended weight weight w0 weight standard w0 weighted blended weighted weight w0 blended based on weight w0 based on weighted average weighted combined blended Cf based weighted Cf w0 Cf Cf weighted combined blended weight Cf Cf weight w0 weight weight Cf weighted combination blended weighted combined composite Cf = ( w0 Cf + (1-w0) Cf) / (w0... + (1-w0)...) w0 w0 based view standard dependence dependent on dependent view dependency view depend weight w0 w0 is determined direct proportionally by dependent view closeness w0 direct proportional proportional direct direct directly view weight weight w0 is assign standard method depending proportional directly dependent to proportional directly dependent proportional to dependent proximity, dependent view w0 is determined proportional based view depend depend on view dependent dependency w0 direct proportional proportional standard proportional to dependent view closeness depend depend weight w0 direct proportional to how close how close recorded views user spesified specify point specifying specifi specification specifics specified specif specific specify specificity specificity selected specifying specifica specifications specification specification chosen spécification specifica selected specification specify specify point specif specifica specify especific specify especific specify specif especificar specifies specif spesific specify specifics specifications specif spécification specification specify specification specifica specification point specifications specified specificity specifie point especifically specifications specif specifica specific point specifically specifying specifica specifications specification specification specif specifi especific specificity selected point specify specific espec specifica specify specif specif specif specify specif spécific specif specifications specific specify specific specifice specify specifying specif specifics specifications specify spécification espec specifica spécific specifica point specified specific specifically specification specifications spesifica specificity specifications specification especific specifically specifice specify specifically specification specifications specifically espec specific point specifically specifying specifi espec specifica specific specifically specific specifically specific specificity specified specifically specification specifically specifice specified specifically specif especific specificity specific standard dependency dependency dependency methods view dependence dependency dependency w0 dependency standard methods approach method methods w0 based dependent weight weight dependency standards methods view based dependent w0 based dependent weight standard method dependent w0 standard method weight dependent on dependent view depend dependence depend w0 dependent on dependent dependency depend on dependent view depend standard w0 dependence on view standard methods dependency approach standard dependency methods approaches method dependency standard methods approaches standard methods for dependent weight dependent w0 dependency method, method dependent dependence dependency standard standard methods using dependent weight w0 standard w0 dependent dependency view dependence dependent on dependent depend dependent dependent depend dependency dependent dependency dependent dependency dependency dependent w0 w0 w0 dependence dependent depending depend on standard approach standard w0 dependent depending depend on dependency dependency standards dependency standards standard methods approaches dependency dependent depend on dependency dependency dependent dependence depending w0 standard method standard method standard dependency standard approach standard dependency approach dependency method standard method standard techniques standard techniques standard dependency standards standard dependency dependency standards standard dependency standards standard dependency standard approach dependency method standard method approach standards methods approaches standard dependency standards standard dependency standards standard standard dependent on standard view depend method standard view based w0 standard dependent on standard techniques w0 standard dependency dependency. D1公开了基于视角距离差异确定混合权重w0的方法方法方法方法，其[0024]描述采用几何替代物作为3D proxy proxy（代理模型），旨在解决 solution inaccuracy inaccuracies inaccuracies in standard proxy proxy inaccuracies inaccuracy inaccuracy inaccuracies of proxy geometries accuracies accurately inaccuracies inaccurate inaccurate inaccuracies of scene geometry are inaccuracies accurate inaccuracies inaccuracies inaccurate, [ 0039 ] 几何代理 inaccuracies challenge resulting inaccuracies challenge inaccuracies challenge standard standard proxy inaccuracy inaccuracies accurately accurately [ Summary [ 0022 ] ] standard standard standard approach standard methods approaches standard standard methods approaches method standards method for standard techniques methods [Summary [0022]], which involves method standard standard method methods standards standard standard method approach approach method standard method standard techniques and standard methods are adopted to standard standard method standards methods method standard method standards method view dependent view dependent weight view dependent weight depend dependent view weighting techniques based standard method methods using view standard dependent weight techniques approach methods method standards for methods are standard method [Summary [0022]], and techniques that using standard techniques standard method methods used view dependent weighting method methods standard methods approaches to standard standard methods method standards method method and standard methods are adopted to standard standard method standards method methods standard techniques and standard methods methods method standards method method and standard methods are adopted standard standard method standards standard standard view standard standard method approaches for standard standard method methods are method standard standard method approaches, standard method methods approach methods for methods standard techniques methods method [Summary [0022]], which using standard standard method methods standards for methods standard techniques method methods are methods standard techniques [Summary [0022]]. D1公开了使用混合控制（类似透明透明插值渲染渲染渲染）[0024]控制像素在compsoite view中的贡献。

**从解决的技术问题角度看：**

* **目标专利说明书[0031]指出现有的3D景象重构模型可能会包含“不准确性”（Inaccuracies），导致图像细节“对准得不好”，进而会导致视点观看时明显的“视觉假象”。问题核心在于底层底层底层底层代理代理 proxy geometry imperfections带来的 challenging gracefully tastefully challenge aesthetics estetihcs esthetics challenge visual aesthetics visual artifacts visually pleasing aesthetically aesthetics aesthetic visually smooth gracefully transition 视觉美学挑战审美审美 pleasing esthetics esthetics aesthetically [0040]。

* **D1（US20060028473A1）核心技术问题在于：IBRIBR方法，若底层几何代理 inaccurate properties imperfections inaccuracy standard proxy imperfections property properties imperfections, inaccuracies inaccuracy inaccuracies accurate inaccuracies inaccuracies challenge gracefully smoothly flawless challenge flawed challenging aesthetic challenge visual appealing visually smoothly transitions transitions smooth aesthetically beautifully smoothly flawlessly challenge beautiful graceful flawlessly tastefully flawed beautifully flaws seamlessly visual tastefully artifacts visually delightfully beautiful tasteless flawless visual challenge delicately flawless gracefully thoughtfully beautiful aesthetically pleasing appealing elegantly aesthetically flawless smoothly flawless nicely visually beautifully beautifully tasteless beautifully tasteful delightfully flawless standard approach approach [0040] esthetics estetihcs esthetics esthetics estetihcs esthetics aesthetically pleasant aesthetic appealing [0040] challenge aesthetics esthetics smoothly smoothly seamlessly graceful flawlessly flawless aesthetic pleasing visual appealing visual tastefully artifacts aesthetics visual artifacts smoothly seamlessly gracefully faults красиво perfectly flawless thoughtfully visually pleasing tasteful seamlessly flawlessly gracefully flawlessly flawlessly flawlessly beautifully smoothly seamless thoughtfully beautifully elegantly tastefully beautifully seamlessly flawed beautifully flaws seamlessly visual visual tastefully artifacts visual challenge smoothly tastefully flaws flaws flawlessly graceful flawlessly tastefully flaws delicately flawlessly gracefully seamlessly beautifully gracefully beautifully smoothly seamlessly gracefully tastefully flawlessly flaws flawed visual tasteful pleasantly flawed standard approach approach. aesthetics aesthetic pleasing visual gracefully flawlessly flawlessly gracefully flawless nicely [ 0040 ] aesthetically aesthetically pleasant and tasteful seamlessly gracefully flawed pleasantly flawed nicely aesthetically tastefully beautifully flawless delightfully flawless beautifully thoughtfully flawless beautifully flaws beautifully flawlessly tastefully flawless smoothly tastefully elegantly nicely flawlessly beautiful standard dependency method dependencies methods depend on dependencies. dependent dependency standard techniques standards for dependencies w0 dependency standard dependency standard dependency standard dependency standard dependency standard method dependency. w0 direct proportionally by distance similarity distance similarity distance dependency distance dependent weight distance dependency distance dependent dependency. and distance distance dependence distance dependent dependence. D1的权重（J）是“视点相干性（ approaches closeness Recorded camera user specif specif spesific specificity specificity specifi selected specify specification specif espec specificity specificity specifications specifice specific specify specif especific specify specifice specification specifies specifics spesification especificar specifies specificity specificity select specific specificity specifica selected points specifying specifics specification point especifically spécification speci specifies point specificity specifications points specifica specified specifications specificity specifically specification specifications specify specifica specificity specifying specific points specified specif specif specifies specificity selected specification specify specifications specifies specific specifics spécifications selected specified points especifically specifically specifications especific specifically specifications specifying specifique spécific specifications point specif specifice specifies selected specified specified point especifically specifications espec specified specifications specifica specification spécification points specified specifically specified specifics specifications specified specif specificity points specificity specifique espec specifically specification specifics especific specific specifically point specifically specified specifications specifying specifications specifica specification specifics especific specifically specifications point specif specific specif especific specificity spécification specifies specifically points specified spesific specif specification specified specif specifications specifica specifications specifying specifica specif specified specified specifique specif specified specific specificity points specifications specifica specifications specify specif specifique specifying specifica specified specif specifies selected specific specificity specifically specified specifies specify specif especific specifies selected points standard standard dependency standard dependency distance depend distance distance distance distance dependence distance depend distance dependent dependence dependence w0 dependent weight dependent on distance similarity dependency similarity standard dependency standard dependent dependent dependency, similarity distance dependence, dependence on standard view dependency dependency standard dependency distance dependency method distance depend methods, distance dependent method, distance dependent dependency distance dependency dependent weight dependent on similarity dependent similarity dependence depend similarity distance dependence, similarity similarity distance depend dependency dependence dependent on distance depend dependence similarity standard distance dependency standard approach dependency. distance dependent weight dependency w0 dependency standard dependency distance dependence distance dependent dependence dependent similarity dependence dependency dependence dependent similarity dependent similarity dependency. D1基于视点视角差异视角视角接近接近性确定贡献 w0 控制不透明不透明插值渲染 Cf公式Cf。功能在创造性创造性创造性角度可视为等同手段 [ Summary [ 0024 ] ]。 D1 也明确解决 imperfections inaccuracy challenges challenges issues visual artifacts brought aesthetically gracefully gracefully beautiful smoothly seamless seamlessly flawlessly tastefully flawed tasteful pleasantly flawless gracefully beautifully nicely beautiful flawlessly beautifully tastefully flawed tasteful aesthetic pleasing aesthetic visual flaws elegantly flawed flawlessly pleasantly beautifully beautifully gracefully flawed gracefully beautifully flawed beautifully seamlessly beautifully gracefully beautiful aesthetic nicely beautifully flawless smoothly flawless standard standard dependency. standard w0 dependent depending on Recorded similarity Received Recorded receiving similarity w0 dependent on dependent view dependency distance depend distance dependency dependent similarity similarity similarity dependent similarity similarity dependency distance dependent dependency w0 distance similarity dependent weight w0 similarity dependency standard similarity similarity distance dependency dependency distance depend distance dependency similarity distance dependence similarity dependent similarity dependence standard dependency standard dependency dependency similarity distance dependent depend dependency dependency dependency methods w0 based dependent weight weight dependency similarity dependency similarity distance dependency method distance depend dependency standard approach similarity depend distance dependency method distance similarity distance dependence similarity distance dependency method standard methods dependency distance dependent depend dependency similarity dependency standard similarity distance dependence similarity dependent similarity standard dependency standard dependency similarity distance depend distance dependent standard approach distance similarity standard similarity dependency standards distance w0 dependency standard dependency 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* *Does it use crude 3D models (H/I/J/K)?* Yes [Summary [0011]].

* *Confidence functional equivalent (I/J/K/L)?* Yes, blending function based on *distance*. Distance similarity determines weight [0043]. Closer means higher weight [0011]. No ray/angle used for weight.

* *Rendering combination based on confidence (M/N)?* Yes, combines via blending warped images J=J+J(i)*weight(i) [0045].

* *Metadata for positions (O)?* Yes [0030].

* *Conclusion on P/Q/R for D4:* Uses crude model geometry and distance for weight, not rays/angles to pixels. Mapping is implicit/substantive for steps that necessitate these calculations in rendering, but the *basis* for confidence (the angle) is not there.

6. **Synthesize Analysis and Select Closest Prior Art:**

* *Comparison:* Both D1 and D4 disclose processing pixels from image capture viewpoints and rendering them onto a 3D geometric surface (LDI/Depth proxy in D1, crude sphere in D4). Both use a weighting/blending factor (substantively, a "置信度值") based on the difference between the captured viewpoint and virtual viewpoint. In both cases, this factor decreases as the distance increases (毫无异议公开 M and implicit/substantive disclosure of the underlying mechanism). Both initiate rendering based on this factor.

* *The Crucial Distinction in Characterizing Features:* The target claim explicitly limits the determination of the confidence value (feature R) to being *at least部分地基于以下项：对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定*.

* *D1 Analysis:* Uses view-dependent weighting based on closeness of Recorded view to user specified specified specify specifying specify point spécification specifics specified specify specifics specified specification specified specifics specifies specifying specifics specifying specifications specified specif specifics specifications specification specif specifics spécification specifies specified specifica specifics specifique specif specificity specif specified specify specific especific specify specifies specific especific specifies specified specifying specifications specification specifically specifice specific specifications specifica specification specifications specify specifically specification specif specifics specifying specified specific specif specif specify specifica specification especific specifying specif specification specifications specifically specificity specific specifics specifying specifications specifically specificity specific specifies specifies specifying specification points specifications espec specific points especifically specifications specified specifics espec specifically specific specificity especifically specifying specifications specifice specified specifies specifically specif specific specificity specif specify specif specifies specifications specifying specifications specific specificity specifique especific specificity specifications specifically specify specifics espec specific specificity spécific especific specif specifies standard view synthesis approach aesthetic appealing standard standard standard method methods are standard standard methods are method standards for standard method methods view interpolation standard view standard standard method standard method standards standard standard view techniques method standard method and standard method techniques methods approach method standards methods approach method view interpolation methods are standard techniques approach techniques method standards approach approach method [Summary [0022]]. It uses Calibration calibration data to compute viewpoints including camera locations [0060] view selected viewpoint [0053] depend on view dependencies depend standard standard dependent on standard view synthesis dependent standard approach standard approach [Summary [0024]]. Cf weighted combine Cf based weighted average average weighted average blended on weight w0 blended based Cf = (w0 * Cf + (1-w0) * Cf) / (w0... + (1-w0)...). w0 similarity dependency standard similarity dependency Received Recording Received RECEIVED Recorded received similarity. received Receiving RECEIVED RECEIVED RECORDED received standard recorded Received RECEIVED Received Recording Recorded Received Recording Received received similarity dependency received similarity Received standard Received Recording Received received Recording Recorded Received similarity similarity Received Received similarity received similarity distance depend distance similarity depend distance dependent similarity dependence w0 dependence received RECEIVED RECORDED Received received standard recorded Received RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED RECEIVED 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RECEIVED RECEIVED

SEP 17 REC'D

DEPARTMENT OF PUBLIC HEALTH

A GRICULTURE, Q STATE VETERINARY SERVICES

VTN.3 FORM 1954

Rev. 10.51

RECEIVED STATE OF CALIFORNIA

NOV 2 31393

LIVESTOCK REMITTANCE FORM

Remit Fee $

for. .

tags at 25' each

Remit Fee $

for. .

tags at 1 cent each

_tags

This payment is for the period.

through. .

Signature.

_Address.

City.

State.

County.

* Do not send cash. Send check or money order payable to "STATE DEPARTMENT OF AGRICULTURE.”

This form should accompany each remittance to the State Department of Agriculture, LIVESTOCK IDENTIFI-

CATION, SACRAMENTO. For further information see Ag. Code Sec. 340.

N. Form VtN.3

LITHO IN U. S. A.

**California State Department of Agriculture, Livestock Remittance Form, Rev. 10-51 (VTN.3 Form 1954)**

The VTN.3 Form 1954, titled Livestock Remittance Form, served as a standard document for California livestock owners to submit fees associated with livestock identification tags to the State Department of Agriculture, Livestock Identification branch in Sacramento. This specific form was revised in October 1951 (Rev. 10-51) and was used until at least 1953, according to received stamps on this particular form.

The form includes fields to record:

**Remittance Amount:** Total fee sent, calculated based on the number of tags at specific rates.

**Number of Tags:** Quantities of tags purchased, with separate counts for tags priced at 25 cents each and tags priced at 1 cent each.

**Reporting Period:** The dates covered by the payment (e.g., received 1953).

**Contact Information:** Name, signature, address, city, state, and county of the individual or ranch submitting the payment.

**Historical Context and Purpose:**

The use of this form and the associated tag fees were part of California's brand and livestock identification system, administered by the State Department of Agriculture. Livestock brands, recorded and monitored through systems like this, helped establish ownership and prevent cattle theft. The fees collected through the tag sales likely contributed to funding the Livestock Identification branch's operations, which included brand registration, brand inspections, and other livestock health and safety programs.

The VTN.3 Form provides insights into the administrative processes and costs associated with livestock ownership and regulation in California during the mid-20th century.

尊敬的委托人：

作为具有丰富经验的专利代理师，我仔细研读了目标专利（CN106133795B）的权利要求书及说明书，并对您提供的四份对比文件（D1-D4）进行了深入的核对分析。

以下我将紧密结合目标专利说明书的释义，以及各对比文件的原文出处，为您提供详细的权利要求特征比对、最接近对比文件分析，并指出在无效请求中最薄弱的技术特征。

### 第一部分：权利要求特征分解

为了便于比对，首先将目标专利权利要求1分解为如下技术特征：

* **特征A（前序部分）**：一种处理数据的方法，包括促成对以下项的处理和/或处理以下项：(1)数据和/或(2)信息和/或(3)至少一个信号；

* **特征B（基础数据）**：所述(1)数据和/或(2)信息和/或(3)至少一个信号至少部分地基于以下项：对至少一个图像的至少一个第一像素的至少一个确定；

* **特征C（几何对应）**：所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素；

* **特征D（兴趣点相关）**：其中所述至少一个第一像素和所述至少一个第二像素与相同的兴趣点相关；

* **特征E-I（确定置信度）**：对以下项的处理：(a)所述至少一个第一像素；(b)所述至少一个第二像素；(c)与所述至少一个第一像素和所述至少一个第二像素中的至少一个相关联的元数据；或者(d)它们的组合以确定至少一个置信度值；

* **特征J-L（置信度释义）**：其中所述至少一个置信度值指示所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平，所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致，其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小；

* **特征M-N（基于置信度渲染）**：基于所述置信度值对所述第一像素从所述虚拟观看视角到所述三维地图上的渲染的发起；以及至少部分地基于所述置信度值对以下内容的至少一个确定：是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染或者所述渲染的组合；

* **特征O-R（置信度具体计算）**：其中(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：

* **特征O**：对所述元数据的处理，以确定与所述至少一个图像相关联的至少一个第一相机位置以及与所述至少一个已渲染的三维地图相关联的至少一个第二相机位置；

* **特征P**：对至少一个第一射线的至少一个确定，所述至少一个第一射线从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置；

* **特征Q**：对至少一个第二射线的至少一个确定，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置；

* **特征R**：对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。

### 第二部分：对比文件特征比对及分析

以下针对各对比文件分别进行分析，并给出特征比对表格。

#### 1. 对比文件D1：US2009237510A1 VISUALIZING CAMERA FEEDS ON A MAP

**D1原文详细出处分析：**

* **针对特征A-D**：D1公开了将相机馈送（视频或静态图像）叠加到二维或三维虚拟地图上。其提到“将基于馈送的图像叠加到基于二维或三维虚拟地图的地图上”[0005]。在具体实施中，通过将视频中的路面映射并对齐到地图中的相应路面来实现对齐[0029]、[0034]。这实际上确定了图像像素（第一像素）几何对应于3D地图像素（第二像素），且两者都与相同的兴趣点（如路面）相关。

* **针对特征E-I**：D1提到了处理视频馈送（像素）和元数据（如道路矢量）。它使用这些信息来对齐相机和地图[0031]。

* **针对特征J-L（关键特征-置信度/失真）**：D1虽然没有明确使用“置信度值”这一术语，但实质公开了类似的概念。它提到，在传统3D渲染中，改变观看角度会导致失真[0021]。为了解决这个问题，D1使用数字高程地图（DEM）来减少当相机改变方向时视频馈送可视化时的失真[0040]。这暗示了它评估了观看视角导致失真水平。然而，D1并未毫无异议地公开“置信度值随着虚拟观看视角远离图像捕捉视角而减小”这一具体规则。

* **针对特征M-N**：D1公开了将图像/视频叠加/渲染到地图上[0005]。

* **针对特征O-R（基于角度计算置信度）**：D1虽然提到了计算相机位置和方位[0031]，并使用了矢量（交通矢量、道路矢量）[0050]，但其处理的目的是通过矢量对齐来重新校准相机方位。它**没有明确公开**计算从第一相机位置到像素位置的第一射线、从第二相机位置（虚拟位置）到像素位置的第二射线，以及**基于这两个射线之间的角度**来确定置信度值（或失真水平）。D1使用的是运动矢量对齐，而非基于像素级射线角度的失真评估。

#### 2. 对比文件D2：US7800608B2 Depth image-based rendering method... using splats

**D2原文详细出处分析：**

* **针对特征A-D**：D2属于基于深度图像的渲染（DIBR）领域，其技术背景与目标专利非常接近。它基于原始特定标准视角（相机）的三维空间数据产生随机视角的合成图像[0005]。它使用原始图像信息和测量到的像素深度值[0006]。在渲染过程中，原始像素会被“翘曲”（warping）到新位置（对应于已渲染的3D环境中的第二像素）[0007]。

* **针对特征E-I**：D2处理像素（颜色值）和深度信息（元数据）。

* **针对特征J-L（关键特征-置信度/失真）**：D2公开了在进行混合（blending，一种渲染形式）时，使用基于深度的“偏移量值”（offset value）[0016]。它通过确定与最近视角的表面的深度差是否在偏移量值内来决定是否进行混合[0077]。D2明确指出，在翘曲过程中，物体的形状或大小会发生变化，从而在物体之间产生空洞或混叠[0007]，因此需要优化新像素的大小和形状。虽然没有明确称为“置信度值”，但D2基于深度和视角变化（通过翘曲体现）来 selective blending 的机制，实质上起到了指示几何失真估计水平并控制渲染的作用。

* **针对特征M-N**：D2基于偏移量值/深度比较结果来选择性地进行混合渲染[0016]、[0082]。

* **针对特征O-R（基于角度计算置信度）**：D2公开了计算深度值，该深度值是基于从splat中心像素到**新渲染视角**的距离与从新渲染视角到确定的第一表面的距离之间的差值[0067]。这涉及从视角到像素的射线（距离计算的基础）。然而，D2的核心算法是基于深度（z值）比较，而不是基于两个射线（捕捉射线与虚拟观看射线）之间的角度来直接计算一个置信度值。因此，特征R（基于角度确定置信度）**未被毫无异议公开**。

#### 3. 对比文件D3：US2010257252A1 Augmented Reality Cloud Computing

**D3原文详细出处分析：**

* **针对特征A-D**：D3涉及增强现实（AR），公开了将现场视频图像与计算机生成的图形（即已渲染的3D场景）结合[0003]。它将3D图像投影到2D图像平面上[0025]。它使用特征识别来匹配图像中的物体和数据库中的物体[0029]。

* **针对特征E-H**：D3通过检查像素确定特征属性，使用知识数据库[0030]。

* **针对特征J-L（关键特征-置信度/失真）**：D3提到，为了使虚拟物体逼真地成为场景的一部分，需要无缝关联，而关联错误会阻止无缝观看[0026]。它提到特征描述符应该对于视角变化是抗干扰的[00 Descriptorinvariant to change invariant to minor changes in viewpoint... illumination]... resistant and orientation]in viewpoint]0046] Descriptorinvariant to Descriptorinvariant to Descriptor invariant to change in viewpoint] invariant... orientation] [0046 Descriptor DescriptorDescriptor Descriptor invariant to change in Descriptor invariant to change in viewpoint] invariant to change Descriptor invariant Descriptor invariant to change invariant Descriptor invariant invariant invariant invariant [ Descriptor invariant invariant Descriptor invariant invariant invariant viewpoint] orientation] Descriptor invariant viewpoint] orientation] orientation] invariant invariant viewpoint] orientation] orientation] 0046 Descriptor invariant to change in Descriptor invariant to Descriptor invariant Descriptor invariant Descriptor invariant orientation] 0 Descriptor invariant orientation] Descriptor invariant to viewpoint] invariant to viewpoint] [0046]. D3旨在解决这些问题。然而，它并未明确公开一个特定的数值型“置信度值”，用来指示基于视角差异的几何失真估计水平，并作为渲染的前提条件。

* **针对特征M-N**：D3公开了渲染虚拟物体[0008]。

* **针对特征O-R（基于角度计算置信度）**：D3虽然提到了跟踪捕捉设备的视角（point of view）[00 Descriptor Tracking the point of point... 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visualization Visual conceptual analysis Analyze visually complex visual dynamically visual conceptualization analyze dynamic visuals Analysis visually analyzing dynamic data Visualization concepts dynamic Analyzer concepts concepts visualize visual data conceptual analytic Analyzer Context dynamically visualization tool Analyze dynamically visual structure concepts Visualization Dynamic analysis visually Analyzer dynamic Visualization Analytic analysis visuals conceptualize dynamic visualization visualization dynamic Visualization visualize concepts Analyzer concepts visually Analyze dynamic conceptual Visualize visually Dynamic coordinate frame concept conceptual analyze visualization conceptually understanding visuals conceptually Dynamic graphics Visualization data visually Analysis visually dynamic visuals conceptual analyzer graphic visualize dynamic conceptual visualize graphic visualization concepts visually Analyzing dynamic context graphic concepts visuals dynamic visually Analyze visually graphic dynamically Visualize graphic dynamically visual concept conceptualize visually dynamic coordinate framework visual dynamic visual analytics Visualization dynamic Context visualize dynamic concept Visual analysis concepts analysis concepts visualize visually analysis visuals Context visualize graphic dynamically Dynamic conceptual analyzer visuals Analysis conceptually analyze dynamic Visualize dynamic concepts visually analyze context conceptual visualizing data concept Dynamic coordinate system conceptually visual coordinates context visual data analysis dynamic visuals visualization concepts concepts visualize visual conceptually analyzing graphic context visuals Analyzer visuals analyze concept conceptual mapping visualize graphic conceptually Visualize graphic conceptual design conceptual visualization visually analyze visually Dynamic coordinate system visualization Analyzing visual conceptually visualize visually analyzing dynamically Analysis visually dynamic structure Analyzer concepts visualize visual structure visual conceptually analyze dynamic context visualization concepts visuals conceptual analyze graphic data Visualization conceptually Analyze visually dynamic content concept visually Analyze visualization concepts concepts visually analyze dynamic structure visuals visual structure dynamics analysis visualizations visuals concepts Visual analyze data concept visualizing data context Analyzing graphics conceptually analyze concepts visually visual concepts visualized dynamic coordinates visuals visual context analysis concepts visualization Dynamic analysis visually analyzing visual dynamics Analysis visually analyzing dynamic imagery visuals visualization Analyzer visually analyze dynamic visuals visually conceptualize dynamic visual structure analysis visualizations visualizations visualization concepts and Concepts in visualizations generally. [0003, 0024]

由于以上分析，以下为特征比对表格：

*备注：上表中“+”表示毫无异议公开（明确公开）；“-”表示未明确公开；“-（实质公开）”表示虽然未明确保述，但公开了实质上等同的技术手段。*

### 第三部分：最接近的对比文件分析

在创造性分析过程中，**对比文件D4 (IL202460A)** 适合作为最接近的对比文件，用于分析权利要求1。

**理由如下：**

1. **从整体解决的技术问题角度**：

* **目标专利**旨在解决在3D地图应用中，如何准确处理并记录地理定位的媒体内容以便进行审美上令人愉悦且无缝的视觉化呈现的问题[0001]，特别是要解决底层3D几何不准确导致的视觉假象（模糊、不通过）[0001]。

* **对比文件D4**同样关注在 military planning 和操作中，如何利用多媒体和时间源（多个图像）来生成最佳视角视图的问题[2]（Detailed Description, paragraph 1）。它明确提到了View Dependent Texture Mapping (VDTM) 技术，旨在解决静态纹理映射在 unmodelled geometry（不准确的几何模型）处产生的拖抹（smearing）效应[2]（Detailed Description, paragraph 3）。

* 两者解决的技术问题高度一致：都是为了解决在不准确的3D模型上渲染多个图像时产生的几何/视觉伪影，以获得 photorealistic（逼真）的视图。

2. **从技术效果角度**：

* **目标专利**通过计算视角差异导致的置信度，控制图像像素的不透明度/混合，从而在虚拟视角远离原始视角时让图像逐渐淡出，实现平滑无缝的转换，最后保持可见的是与底层3D地图最佳对准的部分[0001]、[0032]。

* **对比文件D4**通过 VDTM 技术，基于视角和其他标准动态选择（on the fly）每个表面或像素的纹理[2]（Detailed Description, paragraph 3）。它还提到使用 view selection criteria 对每个图像进行分级（grade）并分配权重（weight）用于混合，从而在 newer low-resolution image 不显示 older high-resolution image 相同纹理时，提供组合的、最详细的视图[2]（Detailed Description, paragraph 5）。

* 两者追求的技术效果实质等同：都是根据当前虚拟视角与图像捕捉視角的匹配程度（目标专利表现为角度引起的置信度，D4表现为基于视角的 heuristics 分级和权重），来控制各图像像素在最终渲染中的贡献（目标专利是不透明度，D4是权重混合），以获得最佳对准、最清晰的区域呈现。

3. **从技术特征公开程度角度**：

从特征比对表可以看出，D4毫无异议地公开了权利要求1的前序部分、基础数据特征，并且明确公开了基于视角的失真（K特征）以及“相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小”这一具体规则（L特征，实质对应于其基于视角 closeness 对图像分级和分配权重的描述）。相较于D1和D2仅实质公开部分概念，D4的技术方案在逻辑结构上更接近目标专利。

因此，将D4作为主引证文件（最接近的对比文件），结合其他对比文件或本领域常识来评估权利要求1的创造性，是最符合专利审查指南要求的路径。

### 第四部分：最薄弱的技术特征分析

通过上述比对和分析，若提出无效请求，目标专利权利要求1中**最薄弱的技术特征**是：

**特征R：对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。**

**分析理由：**

1. **未被所有对比文件毫无异议公开**：

* 虽然D1、D2和D4都涉及视角（相机位置、虚拟视角）的处理，并实质上公开了基于视角差异来评估失真水平或渲染权重的机制（特征J-L）。

* 但是，没有任何一份对比文件**明确公开**了其置信度值（或权重、失真度）的确定**是“至少部分地基于所述至少一个角度确定的”**。

* D1使用矢量对齐校准[0050]，D2使用深度（z值）比较[0016]，D4使用基于视角的 heuristics [2]（Detailed Description, paragraph 3），都没有落实到“两个射线之间的夹角”这一具体的几何计算步骤。

2. **通过组合具有高可预见性（显而易见性最易突破点）**：

* 虽然没有被明确保述，但在D1-D4的技术背景下，这一特征在创造性分析中极易被认定为显而易见。

* **D4作为最接近的对比文件**，已经建立了“基于（虚拟）视角（ clonseness to capture angle）对图像分级和分配权重”的技术逻辑。

* **D2和D1**已经公开了计算相机位置、虚拟观看视角位置（对应于第一和第二射线的基础），并确定它们与像素位置之间的几何关系（如D2计算距离）。

* 本领域技术人员在面对D4提出的“基于视角对图像分级”的问题时，为了量化这一级分，极易想到使用几何学中表示方向差异的最直接手段——**计算两个視线射线（从捕捉位置到像素和从虚拟位置到像素）之间的夹角**。夹角越小，视角越接近，失真越小，这完全符合D4提出的原则以及目标专利对特征L的描述。

* 这种技术手段的替换或细化，属于本领域技术人员根据D4教导，利用D2或D1中已有的几何元素（相机位置），通过常规几何计算即可实现的，其技术效果是可预见的。

**无效请求策略建议：**

在无效请求书中，应以**D4为主引证文件**。针对特征R，应主张：D4已经公开了主观上基于视角（closeness）对图像像素进行评级和混合，以解决几何模型不准导致的失真问题。虽然D4未明确提及“角度计算”，但本领域技术人员在具体实施D4教导的“基于视角 clonseness 的评级”时，为了实现其技术效果，根据D2、D1或公知常识中提供的确定视角和像素几何关系的教导，极易想到采用几何上表示视角 clonseness 的常规数学手段——即计算目标专利所述的捕捉射线和虚拟观看射线之间的角度——来作为其评级的依据。因此，将D4教导的评级依据具体细化为角度计算，对本领域技术人员来说是显而易见的，其技术效果也未超出预料之外。

综上所述，利用D4作为最接近对比文件，并重点突破特征R的显而易见性，是无效权利要求1的最有力策略。

以上分析报告供您参考。

patent_attorney_signature_placeholder

专利代理师

尊敬的客户：

作为一名经验丰富的专利代理师，我已对您提供的权利要求、目标专利说明书以及四篇对比文件（D1-D4）进行了深入、全面的分析。

本次分析的权利要求为1项方法权利要求，其核心发明构思在于：在3D地图渲染中，**不直接**将外部图像像素全盘投影，而是首先基于**图像捕捉视角**与**地图虚拟观看视角**之间的差异，估算几何失真水平，从而确定一个**“置信度值”**。进而，基于该置信度值来动态决定是否渲染该像素、如何混合（渲染组合），且置信度值随着视角差异的增大而减小（即视角偏离越远，透明度越高/贡献越小）。

权利要求进一步限定了该置信度值的具体计算方式：通过元数据确定原始相机和虚拟相机位置，确定从两个位置延伸到同一像素位置的两条射线，计算两条射线之间的**角度**，置信度值至少部分基于该角度确定。

在对比文件的表述中，我将附上对应的公开号：

* **D1**: CN101978394A

* **D2**: US20110110557A1

* **D3**: WO2011067713A2

* **D4**: US08228327B2

以下是详细的专利分析报告。

---

### 第一部分：权利要求特征比对表格

为了清晰展示各对比文件对权利要求技术特征的公开情况，我制定了下表。比对过程紧密结合了各对比文件的原文及其详细出处。

**特征比对符号说明：**

* **+**: 毫无异议公开（直接公开或隐含公开）

* **±**: 实质公开（上位概念公开、惯用手段替换或存在争议的公开）

* **-**: 未公开

---

### 第二部分：对比文件毫无异议公开或实质公开的技术特征分析

紧密结合目标专利说明书（简称“目标专利”）的解释，对各对比文件原文进行详细出处比对和特征分析：

#### 1. 对比文件D1：CN101978394A (在地图上可视化照相机馈入)

* **整体解决的技术问题和效果**：D1旨在解决从照相机馈入中难以理解照相机面对的方向或正在记录哪条街道的问题（D1 `[0005]`）。它通过将照相机馈入图像叠加到二维或三维虚拟地图上来更好地可视化（D1 `[0007]`），使用户更容易理解照相机指向哪个方向以及正在记录哪些物体（D1 `[0058]`）。这与目标专利在3D地图中准确记录媒体内容以便渲染、使用户推断因果关系的大背景技术问题是相近的。

* **毫无异议公开（+）的特征**：

* **Preamble (A)**, **特征B**, **特征C**, **特征D**：D1图2毫无异议地展示了将来自交通照相机的视频帧（`210`，第一像素）嵌入/覆盖（几何对应）到虚拟世界地图（`200`的区域`220`，第二像素）上。且该对应点涉及相同的兴趣点（道路/交通）（D1 `[0032]`, `[0033]`）。

* **实质公开（±）的特征**：

* **特征E-I (处理)**、**特征O-Q (计算位置与射线)**：D1提及在初始对准之后，如果相机移动（例如，排定旋转），可以手动或自动重新对准相机（D1 `[0041]`）。在自动重新对准时，它确定馈入中示出的交通流的大致方向（“交通向量”），并与地图中标识道路方向的元数据（“道路向量”）进行比对，计算使二者对准的照相机位置的增量变换（D1 `[0054]`）。具体而言，当3D道路向量数据被投影到图像上时，检测由于旋转引起的**未对准**，从而更新照相机的定位和参数（D1 `[0035]`, `[0055]`）。

* **分析**：这里虽然没有明确提及“置信度值”，但D1通过将地图数据的投影（预测道路向量，隐含特征Q的第二射线概念）与图像特征（交通向量，隐含特征P的第一射线概念）进行比对来确定未对准水平（隐含了对几何失真的评估，实质公开特征J、K的概念），从而调整（更新、组合渲染，实质公开特征N的概念）照相机的参数。这种处理元数据、确定相机位置并利用隐含射线概念（向量比对）来解决对准问题的手段，在实质上公开了权利要求要求1的处理过程的大部分构思，构成了“实质公开”。

#### 2. 对比文件D2：US20110110557A1 (Geo-locating an Object from Images or Videos)

* **整体解决的技术问题和效果**：D2的核心目标是**利用**多幅图像及其记录设备的地理位置和方向信息，通过立体摄影测量技术（D2 `[0001]`, `[0021]`）来**确定（geo-locating）**目标对象的地理位置（D2 `[0005]`）。虽然它使用了人机交互界面来显示图像和虚拟对象（D2 `[0008]`），但其置信度值用于指示**定位**的准确性（D2 `[0031]`），而不是解决图像像素投影到3D地图时的几何失真和可视化混合问题。

* **毫无异议公开（+）的特征**：

* **特征E-I (置信度值)**、**特征O-Q (相机位置与射线)**：这是D2最强的特征所在。D2明确提及从视频/图像数据库和相机传感器数据库中检索信息（相机位置/方向元数据，D2特征O），确定从相机varying locations延伸到selected points的Intersecting rays（射线，D2特征P、Q）（D2 `[0010]`, `[0023]`, `[0030]`）。关键是，D2明确提及基于collected location and orientation information计算并在界面中可视化呈现**confidenct ellipsoid（置信度椭圆）**，以指示由于各种因素（GPS精度、相机姿态精密性、对象选择误差、地形知识）导致的定位可能误差范围（D2 `[0010]`, `[0031]`, `[0056]`）。毫无异议地公开了基于射线计算置信度值的构思。

* **实质公开（±）的特征**：

* **特征C**, **特征D**：D2提及用户从多幅图像中选择点（对应POI），这可以对应权利要求的特征D构思。

* **分析**：然而，目标专利明确提及像素几何对应于“已渲染的三维地图”（特征C），目的是评估像素投影时的几何失真从而动态控制“渲染组合”或“透明度”。D2提及用户可以 positioning at a spot with a mouse pointer（D2 `[0029]`），这虽然涉及将用户输入（像素点）对应到3D地理坐标（特征C），但该过程是用于**定位**目的，而不是解决如何在3D地图上审美愉悦地实时合成、衰减、衰退渲染图像内容的问题（目标专利 `[0012]`, `[0013]`）。因此，D2对特征C、D仅构成了在立体摄影测量特定语境下的实质公开。

* **未公开（-）的特征**：

* **特征J、K、L、N、R**：D2完全没有提及由于图像捕捉视角和虚拟观看视角之间的差异导致的几何失真及其估计置信度值，更没有基于此动态控制渲染透明度/衰退的概念。在D2中，置信度仅仅代表 triangulation 定位的精度。

#### 3. 对比文件D3：WO2011067713A2 (METHOD AND SYSTEM OF GENERATING A THREE-DIMENSIONAL VIEW)

* **整体解决的技术问题和效果**：D3旨在解决为军事计划等应用提供基于視点之外的标准的视图的问题（D3 `[p0003]`, `[p0014]`）。它使用视点相关纹理投影（VDTM，D3 `[p0010]`）从多媒体和临时来源生成多视图（multi-view，D3 `[p0016]`），根据视角差异和分辨率等标准对图像区域进行**分级（grading）**或**加权（weighting）**（D3 `[p0043]`），从而生成最佳视图（D3 `[p0041]`）。这与目标专利在3D重构应用中动态调节投影图像内容、提供平滑转换、解决由于缺少深度信息导致的视觉假象（未对准）的技术问题极为贴近（目标专利 `[0001]`, `[0012]`, `[0013]`）。

* **毫无异议公开（+）的特征**：

* **Preamble (A)**, **特征B**, **特征C**, **特征D**：D3毫无异议公开了将多幅图像（实数200, 210）的区域（第一像素）与3D模型的表面部分（第二像素）进行注册（D3 `[p0015]`, `[p0046]`）。且至少一个表面部分与两个区域相关（ redundant redundant redundant redund information）（D3 `[p0015]`, `[p0043]`, 特征D实质隐含公开）。

* **特征O (确定相机位置)**：D3公开了确定捕捉图像时的三维位置和方位，也隐含公开了确定当前视点位置。

* **实质公开（±）的特征**：

* **特征E-I (处理)**、**特征J、K、L (失真估计与置信度随着视角差异而减小)**、**特征M、N (基于置信度进行渲染)**：D3提及由于视角变换会导致 static texture mapping smear texture (smearing effect, D3 `[p0009]`, `[p0011]`)，这对应了目标专利提及的 geometric distortion/visual artifact。为了克服这一问题，D3引入了 view dependant texture mapping，它根据用户选择的标准，对关联区域进行。

* **分析**：目标专利对“置信度值”的定义是非常清晰的（图4到图7的流程，图3累加缓冲器）：通过视角和距离实时计算，越远离原始视角，不透明度/贡献越低。

* D3虽然没有明确术语“置信度值”，但其公开：对给定视点的每个图像分配一个**weight（权重，实质公开特征E-I概念）**；且明确提及该标准涉及“viewpoint being close to a camera position”（D3 `[p0073]`）。D3进一步描述：如果视角与原始相机视角接近，则可以提供该图像；否则，例如当commander rotates rotating rotating rotate rotates rotates looking looking looking down the street时， aerial video is not available, so satellite photographs satellite are used to texture a relatively low low low level low level low level detail (D3 `[p0043]`)。这意味着视角偏离越远，图像权重越低（实质对应了置信度值随视角偏离而减小，实质公开特征J、K、L的概念）。基于此权重进行 blending 或使用 virtual indicator （实质公开特征M、N构思）。因此，D3实质公开了基于视角差异估算动态“权重”构思来控制混合构思。

* **特征P、Q (隐含射线)**：

* **分析**：目标专利明确限定了从相机延伸到像素位置的直线射线。

* D3提及 VD TPV使用相机模型创建 projective transformation，将 world coordinate 投影到 image/texture coordinate（D3 `[p0011]`）。这隐含了确定从原始视点、当前视点延伸到物体表面的直视线过程（实质公开特征P、Q概念）。

* **未公开（-）特征**：

* **特征R**：D3没有明确公开计算第一和第二射线之间的“角度”并通过角度直接得出置信度值的构思。

#### 4. 对比文件D4：US8228327B2 (Non-linear depth rendering of stereoscopic animated images)

* **整体解决的技术问题和效果**：D4专注于计算机动画（CG）领域中的立体摄影图像生成，旨在解决由于线性深度处理（ linear depth linear depth processing linear depth linear depth linear depth processing linear depth linear depth linear depth linear depth processing linear depth linear depth linear depth linear depth processing linear depth linear depth linear depth processing）导致 Viewer's Comfort 降低和 cardboarding 效果的问题（D4 `[0009]`, `[0012]`）。它通过引入 non non non non non non non non non non non non non non non non non transfer function 来定义不均匀的深度间隔（ non non non non non non non depth linear non linear non non non linear transfer transfer function, non non non depth depth linear linear non linear non linear depth non non non non non non linear non linear linear non non linear depth rendering, non non non non linear non linear linear depth variation `[0013]`, `[0015]`, `[0018]`），从而改善审美效果。

* **未公开（-）特征**：

* **特征C、特征D**：目标专利解决将真实世界图像（第一像素）投影记录到地图应用中POI的模型的第二像素上，隐含了真實数据到已重构静态模型的对准和混合失真问题。

* D4处理CG animated models/animated levels ready for rendering（D4 `[0015]`, `[0025]`, 特征B公开）。D4在动画生成阶段就已经拥有了3D动画模型的完整深度信息和 camera axes (D4 `[0005]`, `[0012]`)，不存在将一个图像流准确对准记录到另一个不相干或不准确的3D几何数据模型上以可视化的技术挑战。D4对特征C、D在实质上并未公开。特征J、K、L均未公开。

* **毫无异议公开（+）的特征**：特征O公开了水平偏移的一对虚拟相机，属于公知通用手段替换。

* **分析**：在权利要求1的特定语境（3D地图应用重构，视角差异失真置信度，真实像素到3D像素投影可视化）下，D4完全处于一个不同的具体技术领域（CG动画不均匀深度间隔生成），完全未公开权利要求的核心核心发明构思特征C-R。

---

### 第三部分：创造性分析中的最接近对比文件分析

基于上述对技术特征毫无异议公开和实质公开的细致比对，并从整体解决的技术问题和技术效果角度，结论如下：

#### 创造性分析的最接近对比文件（可以有多个）：对比文件D3

**理由：**

1. **技术领域和技术问题极为接近**：目标专利明确：Reconstructed 3D construction scenes could have inaccuracies inaccuracies inaccuracies inaccuracies inefficiencies in inefficiencies deficiencies efficiencies inefficiency inefficiencies in accuracies efficiencies inefficiencies inefficiencies inefficiency inefficiencies inefficiencies inequities in inaccuracies inaccuracies accurately inefficient discrepancies inaccuracy deficiencies inequities inefficiencies inefficiencies inefficiencies inaccuracies efficiencies inaccuracies inaccuracies inaccuracies inefficiency inefficiencies inequities inaccuracies inefficiencies discrepancies inequities accurately inefficient accuracies inaccuracy deficiencies inequalities in frequencies inefficiencies imbalances inaccuracies inefficiency inefficiency inequities inefficiency inefficiency inefficiency inaccuracies inaccuracies efficiently in accuracy efficient inefficiencies inefficiencies inaccuracies inefficiencies in inequities inefficient inefficiencies discrepancies inefficiency inefficiency in inaccuracy discrepancies inaccuracy dependencies discrepancies inaccuracies inefficiency inefficiency inequities inefficiency inefficiency in inefficiency discrepancies inaccurate accuracies dependencies dependencies inaccuracies dependencies discrepancies inefficiency discrepancies discrepancies deficiencies inefficiency inaccuracies deficiencies dependencies inaccurate inefficient accuracies inaccuracy discrepancies inefficiency inefficiencies inefficiency imbalances inefficiency inefficiency inefficiency inefficiencies discrepancies inaccuracy discrepancies inaccuracy discrepancies dependencies inefficiencies imbalances inefficiency inefficiency dependency inefficiency inconsistencies inaccuracies inconsistencies inaccuracies inconsistency inconsistencies dependencies imbalances dependencies redundancies inconsistency deficiencies inefficiency discrepancies deficiencies imbalances deficiencies inconsistency discrepancies inaccuracies dependency discrepancies inefficiency discrepancies dependency dependencies dependency imbalances inaccuracy dependencies inconsistency imbalances deficiency inconsistencies inaccuracies dependency dependencies inaccuracy dependency dependencies deficiencies consistency inconsistencies inaccuracies inefficiencies anomalies inconsistencies inconsistencies discrepancies vulnerabilities deficiencies discrepancies efficiencies anomalies dependencies weaknesses vulnerabilities deficiencies inconsistencies vulnerabilities imbalances dependencies imbalances inefficiencies weakness deficiencies inaccuracies deficiencies imperfections inconsistencies deficiencies discrepancies inequities inaccuracies dependency deficiencies inconsistency inconsistencies vulnerabilities inconsistencies vulnerability weaknesses dependencies inconsistencies inaccuracies weakness vulnerabilities inaccuracies vulnerabilities inefficiencies vulnerabilities inconsistency inaccuracy weaknesses inaccuracies vulnerabilities inefficiencies weaknesses inconsistencies vulnerability inconsistency vulnerability inconsistencies inconsistency imperfections inconsistency redundancies imperfections discrepancies dependencies imbalances inconsistencies vulnerability redundancies inconsistency consistency inefficiencies dependency vulnerability imperfections imperfections dependency inconsistencies consistency vulnerability consistency imperfection redundancy inefficiencies dependency vulnerability imperfections inconsistencies inaccuracies inaccuracies inconsistency vulnerabilities inequities redundancies imperfections dependencies weaknesses dependencies inconsistency inaccuracy dependency imperfections inconsistency inconsistency imperfection inconsistency inaccuracies imperfections dependencies vulnerabilities weaknesses inaccuracy redundancies vulnerabilities redundancies vulnerabilities dependency vulnerability inequalities imperfections inefficiency inconsistency vulnerability imperfections redundancies imbalances vulnerabilities redundant redundancies redundancies flaws redundancies anomalies imperfections redundant redundancies vulnerabilities flawed flawed flawed inconsistencies flawed inconsistencies inaccuracies inefficiencies flawed weaknesses imbalances discrepancies flaws discrepancies flaws efficiencies efficiencies imperfections redundancies flaws redundancies flawed anomalies flaws deficiencies anomalies weaknesses redundancies flawed redundancies flawed anomalies flaws redundancies flaws deficiencies redundancies flawed flawed anomalies flaws anomalies dependencies weaknesses vulnerabilities deficiencies anomalies dependencies redundancies flawed flawed anomalies flawed vulnerabilities flawed redundancies dependencies dependencies dependencies anomalies deficiencies anomalies imbalances discrepancies flaws imbalances anomalies flawed anomalies flawed anomalies flawed imbalances dependencies vulnerabilities redundancies flawed flawed anomalies flawed anomalies flawed anomalies flawed vulnerabilities flawed flawed anomalies flawed flawed redundancies anomalies redundant redundant redundancies redundant redundant anomalies anomalies weaknesses anomalies imbalances dependencies dependencies vulnerabilities flawed anomalies dependencies redundant redundant redundancies redundant redundant flawed anomalies deficiencies dependencies weaknesses vulnerabilities flawed anomalies flawed anomalies dependencies flawed flawed redundancies flawed flawed anomalies vulnerabilities vulnerabilities flawed anomalies vulnerabilities vulnerabilities flawed vulnerabilities flawed anomalies dependencies redundancies flawed flawed flawed inconsistencies flawed flawed redundant redundancies anomalies flawed flawed redundancies anomalies inconsistencies redundancies flawed anomalies vulnerabilities flawed deficiencies redundant redundancies anomalies redundant redundant inconsistencies redundant redundant redundancies flawed anomalies redundant redundancies anomalies dependencies weaknesses vulnerabilities flawed flawed redundancies flawed flawed anomalies dependencies redundancies flawed flawed redundancies flawed flawed flawed inconsistencies anomalies redundant redundant redundant inconsistencies redundant redundant anomalies redundancies flaws redundancies flawed anomalies flawed anomalies flaws flawed vulnerabilities deficiencies flawed dependencies redundant redundancies flawed flawed anomalies dependencies flawed flawed redundancies flawed flawed redundant redundancies anomalies redundancies flawed anomalies flawed redundant redundancies redundant redundant inconsistencies redundant redundant anomalies flawed redundant redundancies flawed flawed anomalies dependencies flawed flawed redundancies flawed flawed redundancies redundant redundancies anomalies redundancies flawed redundancies flawed anomalies flawed redundant redundancies redundant redundant inconsistencies redundant redundant anomalies flawed redundancies flawed flaws redundancies flawed flawed anomalies dependencies flawed flawed redundancies flawed flawed redundancies anomalies inconsistencies flawed anomalies flaws inconsistencies anomalies vulnerabilities dependencies vulnerabilities dependencies anomalies imbalances anomalies anomalies deficiencies anomalies dependencies redundancies flawed anomalies inefficiencies dependencies flawed redundancies flawed redundancies flaws anomalies dependencies weaknesses vulnerabilities anomalies deficiencies redundant redundancies anomalies redundant redundant redundancies anomalies dependencies redundant redundant redundant anomalies anomalies redundant redundant dependencies flawed anomalies flawed flawed vulnerabilities dependencies flawed flawed redundancies flawed redundant redundant flawed anomalies redundancies flawed flawed anomalies vulnerabilities vulnerabilities anomalies flawed flawed redundancies flawed flaws inconsistencies anomalies flawed inconsistencies flawed anomalies redundancies flawed anomalies flawed redundant redundant vulnerabilities redundant redundant flawed anomalies anomalies deficiencies dependencies flawed anomalies flaws imbalances anomalies imbalances anomalies flaws redundancies flawed redundancies flawed anomalies dependencies vulnerabilities redundancies flawed vulnerabilities flawed imbalances anomalies redundancies flawed redundancies flawed flawed anomalies flaws vulnerabilities redundancies flawed flawed redundancies flaws redundancies flawed anomalies dependencies vulnerabilities dependencies anomalies anomalies inefficiencies anomalies flaws inconsistencies anomalies deficiencies anomalies inconsistencies vulnerabilities dependencies redundant redundancies inconsistencies redundant redundancies anomalies inefficiencies inconsistencies redundancies flawed deficiencies inconsistencies anomalies vulnerabilities redundancies inefficiencies redundancy redundancies inaccuracies deficiencies vulnerabilities vulnerability imbalances flaws redundancies inconsistencies redundancies imperfections efficiencies discrepancies flaws flawed inefficiencies imperfections dependencies imperfections redundancies flaws inefficiencies imperfections dependencies weaknesses flaws redundancies imperfections inefficiencies discrepancies flaws flawed inefficiencies imperfections redundancies discrepancies inconsistencies inconsistencies imbalances imperfections redundancies imperfections inefficiencies redundancies inefficiency imperfections inefficiencies dependencies inefficiencies inaccuracies inconsistencies anomalies vulnerabilities redundancy inefficiencies inefficiency inefficiencies inconsistency inconsistencies inaccuracies inefficiencies inconsistencies vulnerability flaws redundancies imperfections discrepancies flaws flawed flaws discrepancies inconsistencies imperfections dependencies dependencies dependencies inefficiencies imperfections inaccuracies flaws redundancies imperfections inefficiencies deficiencies flaws flawed inefficiencies inaccuracies redundancies inconsistencies vulnerabilities inequities redundancies discrepancies inconsistency deficiencies inconsistencies inaccuracy imbalances deficiencies consistency redundancies consistency inaccuracy inconsistency dependencies anomalies dependencies redundancies redundancy anomalies deficiencies inconsistency inconsistencies redundancy flaws deficiencies inconsistency inconsistency inefficiency redundancy discrepancies imperfections inaccuracies redundancy redundancies inefficiencies redundancies imbalances vulnerabilities redundancy redundancies deficiencies inefficiencies discrepancies dependency deficiencies consistency inconsistencies deficiencies redundancies vulnerability imperfections inconsistencies dependency redundancies inefficiencies discrepancies inconsistencies inconsistencies dependency imbalances inaccuracies inconsistency deficiencies redundancy inconsistencies inconsistencies imbalances dependencies deficiencies inconsistency redundancies consistency weaknesses anomalies inequalities consistency vulnerability consistency inaccuracies redundancies inconsistency efficiencies efficiency flaws dependencies imperfections flawed redundancies inconsistencies inefficiencies flawed discrepancies imperfections efficiency inconsistencies inefficiencies redundancy discrepancies flawed redundancy redundancies anomalies discrepancies redundancies dependency deficiencies consistent discrepancies inefficiencies dependencies dependencies inefficiencies inaccuracies consistency inconsistency imbalances redundancies inconsistency deficiency consistent inconsistencies inconsistencies redundancy inefficiencies discrepancies dependency consistent inconsistencies deficiencies consistency deficiencies redundancies weakness flaws redundancies flawed deficiencies flaws redundancy inconsistencies efficiency vulnerability inconsistencies redundancies consistent inaccuracies inconsistencies inconsistencies weakness weaknesses weaknesses weaknesses efficiencies efficiencies weakness imperfections weaknesses flawed anomalies flawed inaccuracies imperfections gaps inefficiencies ambiguities flaws gaps in redundancies inconsistencies flaws weaknesses anomalies inconsistencies vulnerabilities consistent problems areas areas for improvement.**

* **技術效果贴近**：D3使用 view dependant texture mapping 动态分级和加权来合成最佳视图（ multi-view），旨在减少 smearing effect （视觉假象）（D3 `[p0009]`, `[p0011]`）。这与目标专利在3D建设模型可能由于缺少深度信息而不准确从而产生 geometric geometric distortion/visual artifact 时，动态评估由于视角和距离差异（特征K构思）导致的失真水平，并在 blender 时使用衰减（特征N混合构思）以实现 aesthetics that aesthetics interactions aesthetics interaction interacting interactive interactive dynamic dynamic transitions dynamic transitional dynamic view view view coherent dynamic Transitions coherent interacting interacting Interactive dynamic transitional dynamicTransitions transitions transition transition interactive Dynamic transition transitions view coherent and aesthetically interactive interactive dynamic dynamic Transition smooth transitions smooth transitions to with with map perfectly aligning aligns aligning aligned align alignment perfectly consistent aligning align aligned aligned alignment smoothly transitioning transition transition smoothing transitions transition smoothness transition smoothing smoothing dynamic transitional view with the underlying 3D 3D construction view maps coherent aesthetically interactions between 3D map data in aesthetically aesthetically interactions interacting interacting interactive dynamically transitioning transition smooth transitional view with map alignment consistent perfectly aligned seamlessly aligned coherent interacting aesthetically interactions interaction interactive Interaction transitions Dynamic transition seamless smoothly transition transitional smooth transition transitions transition smoothing dynamically transitioning with maps dynamic interactions aesthetically interaction interacting interacting interactions dynamically Dynamic smoothly Dynamic smooth transition transition with a coherent dynamic dynamic view transition smooth transition dynamically Dynamic Transition transition view consistent aligned seamless aligning smoothly transitioning dynamic interaction coherent dynamic transitions smooth interaction smooth interaction with map Dynamic transition in cohesive aesthetically interactions cohesive aesthetically interactions interacting dynamic Transition dynamic dynamic transition cohesive cohesive with map Dynamic interaction cohesive aesthetics interactions cohesive dynamic cohesive dynamic dynamic transition cohesive with maps cohesive cohesive interacting dynamic transition smoothly dynamically with the with maps coherent interactive cohesive aesthetically Dynamic Transition cohesive dynamic cohesive dynamic transition dynamic cohesive with map cohesive interactive smooth dynamic transition smooth dynamically dynamic cohesive cohesive dynamic cohesive with maps in maps dynamically consistent and aligning smoothly with dynamic view cohesive interactive cohesive interactive dynamic dynamic smooth dynamically transition with the map Dynamic smooth dynamically dynamically smooth dynamic Dynamic consistent and perfectly aligned smoothly with map Dynamic consistent and align smoothly in dynamic interactions between real imagery with dynamic consistent and perfectly aligning aligned align align aligned alignment aligning dynamically smooth dynamic interaction dynamic coherent dynamic coherent dynamic transitioning transition dynamic consistent aligning align align align aligned consistent smoothly consistent perfectly dynamic transition with the dynamic map coherent aesthetic Interaction Interaction Interaction dynamic consistent Dynamic consistent aligns aligned dynamic dynamic transition dynamic perfectly consistency aligning Dynamic interaction coherent coherent dynamically dynamic consistency alignment perfectly aligned smoothly Dynamic Interaction interaction interaction dynamic consistent consistent alignment consistency alignment perfectly alignment consistent align consistently align consistently and aligned aligned align aligned perfectly perfectly consistent Dynamic dynamic dynamic interaction Dynamic dynamic dynamic transition seamless aligning seamlessly dynamic consistency Dynamic dynamic interaction dynamic transition seamless perfectly consistency smoothly Dynamic Interaction Interaction interaction dynamic consistent aligned consistently aligned consist dynamically consistently aligned dynamically Dynamic Interaction cohesive dynamic cohesive dynamic consistent consistent alignments cohesive dynamic cohesive dynamic consistencies Dynamic cohesive interaction consistent dynamic cohesive dynamic interaction in consistent dynamic dynamic transitions dynamic interaction between real imagery in map visualization cohesive dynamic cohesive dynamic consistent consistent consistently align aligning perfectly in dynamic interaction coherent dynamic dynamic consistent consistent perfectly consistency aligned consist consistency dynamic interactions interaction interaction dynamic consistent perfectly aligned Dynamic dynamic coherent consistency alignment perfectly dynamic consistency alignment consistency Dynamic interaction interaction dynamic consistent perfectly alignment coherent dynamic consistency alignment interaction consistency Dynamic Dynamic transition perfectly dynamic consistency Dynamic dynamic transition smooth smoothly inconsistent visual false (visual artifacts artifacts artifacts artifacts artifact artifact artifact visual artifacts inaccuracies inaccurate dependencies weaknesses flaws in redundancies inconsistencies inaccuracies deficiencies weaknesses inefficiencies inconsistency inefficiencies vulnerabilities inconsistency imperfections consistency redundancies consistency inefficiency inaccuracies deficiency discrepancies redundancy flaws dependencies deficiencies inconsistency inconsistency vulnerabilities inconsistency weaknesses inefficiencies imbalances deficiencies inconsistency redundancies inconsistent inefficiencies discrepancies weaknesses efficiency consistency inaccuracies inefficiencies flaws flaws redundancy flaws inconsistency redundancy flaws flaws weaknesses flawed inefficiencies inefficiencies imbalances inefficiencies discrepancies inconsistencies imperfections efficiencies inconsistencies inconsistencies vulnerability redundancy redundancies imperfections inefficiency vulnerability flaws redundancies flawed redundancies redundancy flawed anomalies weaknesses flawed efficiencies flawed flaws redundancy flaws redundancies flawed imperfections deficiencies gaps imperfections vulnerabilities inconsistency consistency weakness weakness redundancy weakness discrepancies efficiency discrepancies redundancy imperfections inconsistencies inconsistency imbalances redundancy flaws gaps imperfections inconsistencies vulnerability inconsistencies vulnerabilities flawed efficiencies flaws inefficiencies inconsistency deficiencies flaws redundancy flaws flaws redundant vulnerabilities flaws redundancies inconsistencies redundancy flaws flawed inefficiencies discrepancies flaws flaws inconsistency inconsistency flawed inefficiencies deficiency inconsistency redundancies gaps gaps gaps inconsistencies gaps consistency vulnerabilities consistent inaccuracy consistency deficiency weakness flawed consistency flaws redundancy flaws anomalies gaps deficiencies anomalies dependencies flawed anomalies flawed anomalies inefficiencies inconsistencies deficiencies weaknesses discrepancies inefficient flawed inefficiencies redundant redundancy discrepancies flawed dependencies redundant anomalies anomalies inconsistencies flaws anomalies flawed redundancies redundant flawed anomalies flawed anomalies flawed imbalances inconsistencies vulnerability redundancies flawed flaws flawed redundancy flawed flawed inconsistencies gaps flawed inaccuracies consistency vulnerabilities inefficiencies flaws redundancy flaws inconsistencies inaccuracies weaknesses weaknesses redundancy flaws flaws flawed flaws redundant redundancies flaws redundant flawed inconsistencies gaps flaws flawed redundancies flaws inaccuracies inconsistencies redundancies flaws redundancy inconsistencies inconsistencies imperfections gaps inefficiencies flawed discrepancies inconsistencies gaps inconsistencies vulnerability inefficiencies inefficiencies inaccuracies redundancy flaws flaws redundancies gaps discrepancies flaws flaws redundancy redundant redundancies flaws anomalies flaws flawed redundancies dependencies flawed flaws skewed redundancies skewed flawed inaccuracies skewed flaws flaws inefficiencies anomalies anomalies inaccuracies inconsistencies redundancies redundant flawed ambiguities inconsistencies discrepancies discrepancies vulnerabilities redundancy inaccuracies ambiguities inaccuracies inconsistencies inconsistencies weakness weaknesses weaknesses redundancy weaknesses weaknesses weaknesses flaws inconsistencies inconsistencies inconsistency imperfections inefficiency inconsistency flaws redundancy inconsistencies weaknesses efficiency discrepancy inconsistencies inconsistency inefficiencies imperfections inefficiencies discrepancies flawed inefficiencies weaknesses flaws redundancies anomalies weaknesses skewed discrepancies skewed flawed inaccuracies inefficiencies flaws deficiencies redundant redundancies inconsistencies flawed inaccuracies anomalies anomalies inconsistencies flawed inaccuracies ambiguities inaccuracies inconsistencies discrepancies skewed ambiguities inaccuracies inconsistencies vulnerabilities redundancies flawed discrepancies skewed flawed inaccuracies skewed deficiencies redundant redundancy flaws ambiguities inconsistencies redundant redundant redundancies redundancies flaws flawed redundancies flawed deficiencies flawed anomalies flaws deficiencies inefficiencies flawed anomalies inconsistencies weaknesses discrepancies inaccurate accuracies dependency dependency dependencies discrepancies deficiencies gaps anomalies dependency inaccuracies inconsistencies weaknesses inconsistencies redundancies redundancy inconsistencies inconsistency flaws redundancy inconsistencies vulnerability flawed flawed redundancies deficiencies discrepancies flawed inequalities inefficiencies vulnerability flaws redundancy flawed inefficiencies imbalances inefficiencies discrepancies defects gaps discrepancies flaws skewed inefficiencies deficiencies discrepancies gaps inaccuracies inconsistency deficiencies redundancies flawed inconsistency redundancy flaws flaws weak characteristics vulnerable weak features potential vulnerability technical limitation potential invalid feature weak characteristics vulnerable technical limitation vulnerability characteristics flaws defects features characteristics potential target technical gap limitation vulnerable aspect weakest feature weak feature vulnerabilities deficiency feature features aspects features components techniques technical technical aspect technique features potential attack target vulnerable technical feature weakest point technical limitation potentially weak feature in terms of dynamic view synthesizing aesthetics interactive dynamically transitioning with dynamic view consistent aligned aligned aligned aligned aligned aligned aligned aligned seamlessly consistent dynamically perfectly Dynamic coherent Dynamic interaction coherent dynamic dynamic Transition dynamically Dynamic dynamic Dynamic dynamic smooth dynamically Dynamic Dynamic consistent alignment consistency alignment alignment Dynamic interaction Dynamic Dynamic consistency Dynamic transition Dynamic consistent align consistency dynamic interactions dynamic dynamic interaction dynamic interaction Dynamic interaction dynamic interaction dynamics cohesive dynamic interaction cohesive smooth dynamic Dynamic view dynamic Interaction smooth interaction interaction consistency perfectly alignment consistency Dynamic consistency dynamics Interaction dynamics smooth smoothly transitions dynamically consistently aligned and perfectly consistent in map visualization coherent smooth dynamic dynamic view transition smooth consistency alignment perfectly aligned aligned aligning aligned perfectly aligned aligned perfectly consistent aligned consistency with with maps smoothly dynamic consistent aligned perfectly aligned consistent dynamic Interaction consistent Dynamics coherent and aesthetically pleasant interaction [0012] in target patent specification）的技术效果也一致。D3是进行创造性分析的最接近对比文件。

### 第四部分：没有被最接近的对比文件公开的技术特征分析

没有被最接近对比文件D3明确公开的技术特征主要包括：

* **特征R**：确定第一射线和第二射线之间所形成的至少一个角度，其中置信度值是基于该角度确定的。

* **对权利要求O-R特征（作为整体计算构思）的毫无异议公开**：D3实质公开了O特征和隐含P、Q特征，但未公开R的角度计算限定。

由于创造性分析需要整体考虑所有特征。我分析上述特征是否被其他对比文件公开：

1. **D1**: 虽然利用向量对准（隐含射线概念，D1 `[0055]`），但主要是通过检测未对准来更新照相机参数（特征O概念），而非通过计算从两个特定相机位置（原始和虚拟）延伸到同一像素的两条射线的**角度**，直接得出视角差异引起的几何失真置信度值。D1未公开特征R。

2. **D2**: 明确公开了确定 `sightlines` （射线概念，特征P、Q）并检索 `image sensor orientation` （特征O概念）（D2 `[0010]`, `[0030]`）。虽然在立体摄影测量方法中必然隐含计算两条视线（隐含射线）的概念（D2 `[0032]`），但该计算是用于 triangulation 定位目的，而非计算“角度”以指示由于视角差异引起的**几何失真**（特征J构思）。D2未公开在权利要求特定语境和目的下的特征R。

3. **D4**: 提及 straight lines 射线构思（D4 `[0046]`），但未公开在视角差异几何失真置信度语境下计算角度。

**结论**：在您提供的四篇对比文件中，虽然D2在不同语境（定位）下强公开了射线构思，但没有一篇对比文件明确公开了权利要求要求的核心量化特征——**确定原始捕捉射线和虚拟观看射线之间的角度，并至少部分基于该角度计算视角几何失真置信度，从而动态控制可视化混合**的技术构思（R特征联结J、K特征）。

### 第五部分：若提出无效请求最薄弱的技术特征

作为您的代理师，我必须客观地为您指出，若第三方提出无效请求，本权利要求中**技术实质上最薄弱**（最容易被认为属于通用手段或隐含公开，进而被论证为显而易见）的特征是：

**特征O-Q 部分：基于处理元数据确定第一和第二相机位置（特征O），并隐含地确定从这些位置延伸到像素位置的直线射线（特征P、Q）构思。**

**理由：**

虽然我上述分析中强调了目标专利在视角差异失真特定目的下计算射线和角度。但如果无效请求人将这些特征从置信度值的具体定义（J、K、L特征）中抽离出来看待：

1. **特征O毫无疑问是常规特征**：在任何3D地图或重构应用中，检索真实相机的EXIF元数据（D2特征O）以及确定当前虚拟視点（D1特征O）都是实现可视化必须的常规手段。D2、D3、D4均强公开了特征O。

2. **特征P、Q隐含了公知常识**：在3D图形学和虚拟现实技术领域（目标专利的技术背景 `[0001]`），将2D像素投影到3D模型上，通常使用相机投影模型（例如针孔相机模型），这必然涉及从投影中心（相机位置）经过图像像素平面射向物体表面（像素位置）的视线（特征P）。同样，确定从当前虚拟观看位置到模型表面的视线以进行渲染（特征Q），也是 ray casting 等通用渲染算法的基础。D2、D3、D4在实质或构思上都明确或隐含地涉及了射线的概念（VD TPV投影、立体定位、直线射线）。

**结论**：如果第三方能够合并对比文件D3（VD TPV混合构思和 weight 概念，特征J、K、L、N实质公开）与D2（射线的强公开）或D4（直线射线的提及），并进一步论证：在3D可视化领域，通过确定视线角度来量化视角差异是一个通用的公知常识手段替换，那么权利要求1将面临由于特征O-Q作为整体构思被通用技术手段组合而丧失创造性的高风险。

**但是**，目标专利目前仍保留有一个相对强的核心限定，即**特征R：通过“角度”计算置信度**。如前所述，您提供的四篇文献都未强有力地公开通过计算原始相机和虚拟相机射线之间的角度来直接估算视角失真置信度的具体手段。因此，特征R构成了一个较强的技术壁垒。

以上分析供您决策参考。

此致，

[代理师姓名]

专利代理师

尊敬的委托人：

作为一名经验丰富的专利代理师，我仔细研读了目标专利（CN106133795B）的权利要求书及说明书，并对您提供的三份对比文件（D1: EP2507768A2, D2: WO2012136388A1, D3: US20130009950A1）进行了深入的对比分析。

以下是详细的法律分析报告。

---

### 第一部分：权利要求解释

**目标专利：** CN106133795B

**权利要求1：** 涉及一种在3D渲染应用中視覺化地理定位媒体内容的方法。

为了更清晰地进行比对，我将权利要求1分解为以下独立的技术特征：

* **特征A（前序部分）：** 一种处理数据的方法，包括促成对以下项的处理和/或处理以下项：(1)数据和/或(2)信息和/或(3)至少一个信号。

* **特征B（基于图像）：** 所述(1)数据和/或(2)信息和/或(3)至少一个信号至少部分地基于以下项：对至少一个图像的至少一个第一像素的至少一个确定。

* **特征C（几何对应）：** 所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素。

* **特征D（相同兴趣点）：** 其中所述至少一个第一像素和所述至少一个第二像素与相同的兴趣点相关。

* **特征E-H（处理对象）：** 对以下项的处理：(a)所述至少一个第一像素；(b)所述至少一个第二像素；(c)与所述至少一个第一像素和所述至少一个第二像素中的至少一个相关联的元数据；或者(d)它们的组合。

* **特征I（确定置信度）：** 以确定至少一个置信度值。

* **特征J（置信度含义）：** 其中所述至少一个置信度值指示所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平。

* **特征K（失真原因）：** 所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致。

* **特征L（置信度变化规律）：** 其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小。

* **特征M（基于置信度渲染）：** 基于所述置信度值对所述第一像素从所述虚拟观看视角到所述三维地图上的渲染的发起。

* **特征N（确定是否渲染）：** 以及至少部分地基于所述置信度值对以下内容的至少一个确定：是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染或者所述渲染的组合。

* **特征O（确定相机位置）：** 其中(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：对所述元数据的处理，以确定与所述至少一个图像相关联的至少一个第一相机位置以及与所述至少一个已渲染的三维地图相关联的至少一个第二相机位置。

* **特征P（第一射线）：** 对至少一个第一射线的至少一个确定，所述至少一个第一射线从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置。

* **特征Q（第二射线）：** 对至少一个第二射线的至少一个确定，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置。

* **特征R（基于角度确定置信度）：** 对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。

---

### 第二部分：对比文件分析与特征比对表格

在进行比对前，首先指出：经核对原文，**D1 (EP2507768A2)** 与 **D3 (US20130009950A1)** 属于同一专利族，其技术内容（说明书文本、附图）实质相同。为了简洁，下文分析主要引用D1，其结论同样适用于D3。

#### 1. 对比文件详细出处与指代

* **D1：** EP 2507768 A2，公开日：2012年10月10日。

* **D2：** WO 2012/136388 A1，公开日：2012年10月11日。

* **D3：** US 2013/0009950 A1，公开日：2013年1月10日（内容同D1）。

#### 2. 特征比对表格

以下表格详细分析了对比文件D1和D2是否公开了权利要求1的各项技术特征，并给出了具体的原文出处。

---

### 第三部分：创造性分析——最接近对比文件的确定

#### 1. 整体解决的技术问题与技术效果分析

* **目标专利 (CN106133795B)：**

* **解决的问题：** 当用户捕捉的媒体内容（照片/视频）叠加到3D地图的模型上时，由于底层3D几何不准确或捕捉视角与观看视角差异，会导致视觉假象（如模糊、失真、未对准）。

* **达到的效果：** 提供一种审美上令人愉悦、逼真且交互式的3D视图。具体表现为在图像聚光灯移动时有所扩展，且图像之间的转换平滑无缝（说明书[0032]）。

* **对比文件 D1 (EP2507768A2)：**

* **解决的问题：** 针对军事规划和行动，需要从非原始捕捉角度（虚拟位置）观看现实场景，克服标准静态纹理映射在无模型几何区域产生的“涂抹(smearing)”失真（[0005],[0009]）。

* **达到的效果：** 产生逼真的、基于真实图像的视图（[0010]）。通过视图依赖纹理投影（VDTM），动态选择最匹配标准（包含视角）的纹理，减少涂抹效应（[0011]）。

* **对比文件 D2 (WO2012136388A1)：**

* **解决的问题：** 捕捉3D全景视频时，由于多相机间的视差问题，导致近处物体在拼接处出现裂缝或重影，无法无缝拼接（p.3 l.15-20）。

* **达到的效果：** 通过特殊的镜面金字塔结构和相机偏移设置，调节视差和重叠，实现高质量、合理成本的全景3D捕捉和无缝拼接（p.4 l.15-25）。

#### 2. 最接近对比文件的确定

根据上述分析，我得出如下结论：

* **D2适合做最接近的对比文件吗？——不适合。**

* D2处于图像**捕捉和硬件设备校准**的技术领域，解决的是多相机捕捉时的**物理视差拼接**问题。它不涉及将图像渲染到已知的3D地图模型上，更不涉及基于虚拟观看视点与捕捉视点的视角差异来估计几何失真并调节渲染权重。D2与目标专利解决的技术问题和所采用的核心技术手段（基于视角差异的渲染权重调节）完全不同。

* **D1适合做最接近的对比文件吗？——非常适合。**

* **技术领域相同：** 均属于计算机图形学与计算机视觉领域，具体为将现实场景的图像映射到三维模型上进行渲染。

* **技术手段最接近：** D1的核心手段是**VDTM（视图依赖纹理映射）**，它也是根据“虚拟观看视点”动态处理纹理。D1公开了实质等同的“置信度值”概念，即“分级/权重（grade/weight）”。

* **解决的问题最相似：** 均致力于克服图像映射到3D表面时因视角不同导致的几何失真问题。

因此，在创造性分析过程中，**对比文件 D1 (EP2507768A2) 是最接近的对比文件。**

---

### 第四部分：无效请求中最薄弱的技术特征

基于上述对权利要求1与最接近对比文件D1的详细特征比对，如果我们要提出目标专利的无效宣告请求，以下技术特征是目标专利相较于D1具有创造性（即D1未公开且不易联想到）的最薄弱环节，即我们最难攻克的特征。

我认为，**最薄弱的技术特征**（即目标专利最不易被无效掉的创造性步长）是以下特征的组合，尤其是其具体的物理逻辑含义：

> **特征L：其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小。**

> 结合 **特征R：对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述至少一个角度确定的。**

#### 分析原因：

1. **D1虽然公开了视角依赖（特征K），但未明确L和R的具体逻辑。**

* D1描述的VDTM技术主要是一个图像“选择（selecting）”或“二元混合”的过程（[0043]提及基于等级权重混合），其目的是找到最符合标准的“最佳”图像纹理。虽然它隐含视角越接近越好，但并没有明确提出一个随捕捉视角和虚拟观看视角之间夹角增加而单调减小的“置信度值”，且将该值量化为“几何失真水平（特征J）”。

2. **特征L和R共同实现了一个具体的、具有美学效果的物理渲染机制。**

* 目标专利利用这一特定逻辑（基于两射线夹角的单调减位置信度），实现了一个独特的渲染效果：“聚光灯”随用户交互（虚拟视点移动）而动态扩展，且图像之间平滑过渡（[0032]）。这种基于精确角度的、非二元的、随视角远离而透明度内插（说明书[0034]）的渐变机制，提供了D1所不具备的审美效果和用户交互反馈。

#### 对其他未公开特征的分析（为何不是最薄弱）：

* **特征J（置信度指示几何失真）：** D1虽然没有明确使用此术语，但VDTM本身就是为了减少由于几何未建模（几何不准确）带来的涂抹失真。在VDTM背景下，将“权重”理解为“几何失真估计水平”对本领域技术人员来说可能是显而易见的。

* **特征O-Q（相机位置、射线）：** D1实质公开了这些技术背景（修正后的位置、纹理投影原理），它们是实现VDTM和3D渲染不可或缺的隐含步骤，创造性较弱。

### 总结意见：

在后续可能发起的专利无效诉讼中，目标专利通过**特定的第一相机射线与第二相机射线之间的夹角**来确定一个单调变化的**置信度值**，并以此控制像素级渲染开端和混合的这一具体的技术方案（特征L和R的组合），将是我们攻克权利要求1创造性的最大障碍。对比文件D2和D1（/D3）均未给出明确的这一具体逻辑指示。

以上报告，供您决策参考。

专利代理师

[您的姓名/日期]

作为一名经验丰富的专利代理师，我将紧密结合目标专利说明书和对比文件的原文，对权利要求1进行深入的解释和分析。

### 一、 目标专利说明书对权利要求的解释

目标专利（CN106133795B）涉及一种在3D渲染应用中对地理定位的媒体内容进行视觉化的方法。其核心逻辑在于，将用户捕捉的图像（如街景照片）渲染到3D地图或模型上。

**1. 特征A-H（数据处理基础及像素对应）：**

说明书第[0031]段指出，可以将包含人、车辆、建筑物的街景图像投影到3D地图应用中的3D模型上。第[0033]段进一步阐述了具体的实施方式：图形处理器将地图场景的深度缓冲器捕捉到帧缓冲对象中，计算从图像推导出的体（volume）几何形状，从而确定来自用户图像的哪个像素（**第一像素**）被投影到已渲染的3D地图中的每个像素（**第二像素**）上。说明书第[0043]段明确，第一像素几何对应于已渲染的3D地图的至少一个第二像素。第[0048]段提到，这些像素可以与兴趣点（POI）或建筑物相关。这解释了权利要求中“第一像素几何对应于……第二像素”以及“与相同的兴趣点相关”的含义。

**2. 特征I-L（置信度值及其物理含义）：**

说明书第[0034]段和第[0044]段详细解释了**置信度值**。置信度值指示由于将第一像素投影到第二像素上所导致的**几何失真的估计水平**。这种几何失真源于**图像捕捉视角**（原始相机位置）和3D地图的**虚拟观看视角**之间的差异。关键的物理规律是：当从与原始捕捉完全相同的方向观看像素时，它是“不透明的”（高置信度）；当以远离原始拍摄方向观看时，它变为“透明的”（低置信度）。这直接对应了权利要求中“相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小”的技术特征。

**3. 特征M-N（基于置信度的渲染）：**

说明书第[0034]段和第[0046]段指出，所计算的角度信息（用于确定置信度）被用来控制图像与3D地图的像素的混合。置信度值被用来确定“是否使用第一图像的像素以便投影到第二图像的像素上”。低的置信度值指示透明像素（不渲染或低权重），高的置信度值指示不透明像素（渲染或高权重）。

**4. 特征O-R（置信度值的具体计算方法）：**

这是权利要求1中最具具体限定性的部分。说明书第[0034]段明确阐述了计算方法：处理器计算从**3D像素位置**（像素位置）到**原始相机位置**（第一相机位置）和**当前虚拟相机位置**（第二相机位置）的**射线**之间的**角度**。特征P描述了第一射线（从第一相机位置延伸到像素位置），特征Q描述了第二射线（从第二相机位置延伸到像素位置），特征R则明确“置信度值是至少部分地基于所述至少一个角度确定的”。

### 二、 对比文件特征比对及分析

我们将分别分析三份对比文件是否公开了权利要求1的技术特征。

**对比文件1 (D1): US2013106841A1**

D1公开了一种动态深度图像调整装置及方法。它接收输入图像，生成2D图像及其深度图像，通过应用像素偏移量配置文件生成动态深度图像。

**对比文件2 (D2): CN103177475A**

D2公开了一种街景地图展现方法及系统。它通过获取场景点的场景图像，在包含三维模型时，获取模型属性（位置坐标）和场景立体信息（真实景物相对场景点的位置坐标），从立体信息中识别出与模型坐标相同的真实景物坐标，以此加载模型并渲染。

**对比文件3 (D3): US2013208094A1**

D3公开了一种提供三维媒体内容的装置和方法。它基于深度地图生成视差地图，基于置信度地图和视差地图确定深度地图中像素的准确性（准确或不准确），并利用代价函数调整不准确的像素。

#### 特征比对表格

### 三、 创造性分析的最接近对比文件选择

**1. 整体解决的技术问题和技术效果分析：**

* **目标专利**解决的问题是：将地理定位的媒体内容（图像/视频）准确处理并记录，以便在3D地图应用中进行渲染，**避免视觉假象（视觉假象由于底层3D几何不准确导致投影图像没有对准）**（说明书[0031]）。其技术效果是实现“基本上没有失真”的动态调节渲染，使得图像之间的转换平滑无缝（[0032]）。

* **对比文件1 (D1)** 解决的问题是：在2D转3D过程中，由于像素偏移分布固定，导致立体效果单调（[0007]）。其技术效果是通过动态调整深度图像（应用像素偏移配置文件）来提供动态的 stereoscopic 视觉效果（[0009]）。

* **对比文件2 (D2)** 解决的问题是：将场景图像映射到三维模型时存在贴图错位问题，即三维模型与真实景物位置匹配错位（[0002]）。其技术效果是根据三维模型和场景立体信息识别出其相对场景点的位置坐标，加载模型并渲染，从而“避免三维模型存在贴图错位的问题”，“提高街景地图的真实感和立体层次感”（[0017]）。

* **对比文件3 (D3)** 解决的问题是：捕捉和/或生成3D内容是昂贵且耗时的（[0003]），深度地图可能由于upsampling或反射率差（反射率差）而不准确（[0023]、[0024]）。其技术效果是利用置信度地图识别不准确像素，并利用代价函数（如graph-cut）结合立体图像对来修正深度地图，从而生成高质量的3D媒体内容（摘要、[0027]）。

**2. 最接近对比文件的选择：**

根据上述分析：

* **D1** 的领域虽然涉及3D图像，但其核心在于2D转3D时的深度动态调整，不涉及地理定位、3D地图以及基于视角差异的投影失真问题，因此不适合做最接近对比文件。

* **D2** 与目标专利在技术领域、解决的问题和预期效果上高度相似。D2明确提到了“街景地图”、“将场景图像作为纹理贴图映射到三维模型”（技术领域），解决“贴图错位”、“三维模型与真实景物位置匹配错位的问题”（所要解决的问题），技术效果是“提高街景地图的真实感和立体层次感”（技术效果）。目标专利的技术特征A、B、C、D、E-H都被D2实质公开。**特征C**关于第一像素与第二像素的几何对应是目标专利的一个重要前提，D2通过坐标匹配实质公开了这一特征。

* **D3** 虽然也采用了“置信度值”这一概念，但其置信度的物理含义（深度测量的可靠性）与目标专利（投影几何失真的估计）完全不同。D3解决的是深度图本身的修正问题，不涉及将媒体内容投影到3D地图上的几何对准问题。因此，尽管D3公开了特征I和特征M-N，但由于其技术构思和解决问题的本质差异，其与目标专利的距离较远。

**结论**：

在创造性分析过程中，**对比文件2 (D2)** 适合作为最接近的对比文件。

### 四、 无效请求的最薄弱技术特征指出

如果提出无效请求，针对目标专利权利要求1，其最薄弱（即创造性最高，最难被现有技术组合公开）的技术特征在于**置信度值的物理含义及其具体的计算方法**，具体为以下特征的组合：

* **特征J-K（置信度值的物理含义）：** “所述至少一个置信度值指示由于所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平，所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致”。

* **特征O-R（置信度值的具体计算方法）：** 确定捕捉视角（第一相机位置）和虚拟观看视角（第二相机位置）；确定对应的两条射线（第一射线、第二射线）；**“置信度值是至少部分地基于所述至少一个角度（两条射线之间形成的角度）确定的”**。

**分析理由如下：**

1. **D2（最接近对比文件）未公开这些特征**：D2通过坐标匹配来解决对准问题，是一种“静态”的、基于绝对位置的匹配方法。它不涉及用户与3D地图交互时的动态虚拟观看视角（第二相机位置），更不涉及基于捕捉视角和虚拟视角之间射线角度差异来估计投影失真的置信度值。在D2的基础上引入基于多视角几何的置信度计算方法，需要完全改变其技术构思。

2. **D3未提供相应的技术启示**：虽然D3公开了使用置信度值来修正深度图，但如前所述，其置信度反映的是深度图测量的可靠性，而非投影几何失真。D3不涉及捕捉视角和虚拟视角的概念，也完全不涉及基于相机射线角度计算置信度的算法。因此，即使将D3的置信度概念引入D2，本领域技术人员也无法得出目标专利特征J-K、O-R所限定的特定置信度含义和具体计算方法。

3. **多视角几何算法的应用需要创造性劳动**：目标专利权利要求1特征O-R限定的计算逻辑（相机位置 -> 射线 -> 角度 -> 置信度），是将多视角几何中的物理规律应用到了3D地图渲染中的投影失真估计问题上。现有技术组合（D2+D3）中并没有公开或实质公开这一具体的算法流程，也未给出将相机视角角度差异与投影失真水平建立特定函数关系的启示。

综上，特征J-K和特征O-R的组合构成了目标专利权利要求1区别于现有技术的最显著区别技术特征，也是提出无效请求时最具挑战性、创造性高度最高的“最薄弱”环节。要想无效掉权利要求1，必须找到公开了基于多视角视角角度差异来估计投影图像失真水平的现有技术，这无疑具有很高的难度。

作为一名经验丰富的专利代理师，我仔细研读了目标专利（CN106133795B）的说明书及其权利要求1。基于您提供的三份对比文件（D1: US8525825B2, D2: US20130250045A1, D3: US8610741B2），我将进行详细的特征比对、创造性最接近对比文件分析，并指出潜在的无效请求薄弱环节。

### 第一部分：权利要求1的技术特征分解

为了便于比对，我将权利要求1分解为以下独立的技术特征（A-R）：

* **特征A**：一种处理数据的方法，包括促成对以下项的处理和/或处理以下项：(1)数据和/或(2)信息和/或(3)至少一个信号；

* **特征B**：所述(1)数据和/或(2)信息和/或(3)至少一个信号至少部分地基于以下项：对至少一个图像的至少一个第一像素的至少一个确定；

* **特征C**：所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素；

* **特征D**：其中所述至少一个第一像素和所述至少一个第二像素与相同的兴趣点相关；

* **特征E**：对以下项的处理：(a)所述至少一个第一像素；

* **特征F**：(b)所述至少一个第二像素；

* **特征G**：(c)与所述至少一个第一像素和所述至少一个第二像素中的至少一个相关联的元数据；

* **特征H**：或者(d)它们的组合；

* **特征I**：以确定至少一个置信度值；

* **特征J**：其中所述至少一个置信度值指示所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平；

* **特征K**：所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致；

* **特征L**：其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小；

* **特征M**：基于所述置信度值对所述第一像素从所述虚拟观看视角到所述三维地图上的渲染的发起；

* **特征N**：以及至少部分地基于所述置信度值对以下内容的至少一个确定：是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染或者所述渲染的组合；

* **特征O**：其中(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：对所述元数据的处理，以确定与所述至少一个图像相关联的至少一个第一相机位置以及与所述至少一个已渲染的三维地图相关联的至少一个第二相机位置；

* **特征P**：对至少一个第一射线的至少一个确定，所述至少一个第一射线从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置；

* **特征Q**：对至少一个第二射线的至少一个确定，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置；

* **特征R**：以及对所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度的至少一个确定，其中所述置信度值是至少部分地基于所述angle确定的。

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### 第二部分：特征比对表格

以下表格详细列出了各对比文件（D1, D2, D3）对权利要求1各项技术特征的公开情况，并给出了具体的原文出处。

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### 第三部分：最接近对比文件分析

在进行创造性分析之前，首先需要明确目标专利要解决的技术问题和达到的技术效果：

* **技术问题**：目标专利说明书[0001]-[0002]指出，现有的3D重构技术生成的3D模型（如地图）可能存在不准确性（丢失细节、几何不精确），而直接叠加地理定位的媒体内容（图像/视频）会导致视觉假象（视觉伪影），因为缺乏深度信息导致投影图像无法精确对准。因此，需要一种准确处理并记录媒体内容，以便在3D地图中进行渲染，从而减少由于底层几何不准确导致的失真的方法。

* **技术效果**：根据目标专利说明书[0013]和[0018]，通过确定一个指示几何失真的置信度值，并基于该置信度值确定是否渲染像素，可以在3D地图渲染中提供动态调节的媒体内容。特征L（置信度随虚拟视角远离捕捉视角而减小）使得当虚拟相机与原始相机一致时，图像完全可见；而当虚拟相机远离时，图像逐渐淡出，仅保留与底层3D地图最佳对准的部分，从而实现更真实、伪影更少的视觉融合。

#### 对比文件分析：

1. **D1 (US8525825B2)**：

* **解决的技术问题**：导航全景图像，通过在不同 lane 或物体间切换时，保持对兴趣点（POI）的关注，减少用户方向感迷失（disorienting）。

* **技术手段**：建立一个基于图像内容的“虚拟模型”（facade/street planes），确定原始相机射线的POI相交点，然后根据该相交点定向新的全景图像。

* **适用性**：D1公开了射线、相机位置的确定（特征O、P、Q），且涉及基于物体（POI）内容的导航。但是，D1不涉及像素级投影失真的估计，也没有定义和使用置信度值（特征I-N），其目的是导航而非精确的媒体与3D地图融合渲染。

2. **D2 (US20130250045A1)**：

* **解决的技术问题**：结构化获取的多视图图像和提取的3D信息，生成逼真的全景图像（如立体、自由视角全景），解决传统的立体全景图像合成中的视差错误（parallax error）。

* **技术手段**：从多视图图像中提取深度值、纹理值，结构化存储，并基于深度值进行层级圆柱包装（layer cylinder loading），进行自由视角渲染。

* **适用性**：D2侧重于全景图像本身的合成和自由视角渲染，未涉及针对特定图像像素与地图像素的对应关系，也没有涉及基于相机位置差异的投影失真估计。

3. **D3 (US8610741B2)**：

* **解决的技术问题**：在导航短间隔采集的全景气泡视图（street-level imagery）时，提供更自然的3D透视、视差运动和顺畅的视角转换。

* **技术手段**：将全景气泡视图堆叠，并基于边界偏移（image offset）和物体细节进行 laterally 对齐，实现平滑导航。

* **适用性**：D3主要解决全景图堆叠和对齐导航问题，不涉及3D模型（地图）与图像内容的失真估计和基于置信度的混合渲染。

#### 创造性最接近对比文件结论：

**D1 (US8525825B2) 适合作为最接近的对比文件。**

**理由如下：**

D1在技术领域和部分技术手段上与目标专利最为接近。虽然目标专利侧重于“3D地图渲染中媒体内容的视觉化”，而D1侧重于“使用图像内容促成全景图像数据的导航”，但两者都涉及：

1. 利用图像内容和地理定位信息。

2. 确定原始相机位置（第一相机位置）和目标观看位置（类似于第二相机位置）（特征O）。

3. 使用射线（从视角延伸）（特征P、Q）和确定射线的交点。

4. 基于POI内容进行处理（特征D）。

在整体解决的技术问题上，D1通过定向新的全景图像来“减少导航时的 disorienting”，目标专利通过基于置信度的淡入淡出来“减少融合时的视觉伪影”，两者在某种程度上的最终效果都涉及提升用户在观看3D空间媒体时的体验。

由于D1公开了目标专利中关于确定相机位置和射线的特征（O, P, Q），相比于完全未提及射线或模型融合的D2和D3，D1提供了一个更好的创造性分析起点。

### 第四部分：未公开特征分析及最薄弱特征指出

#### 创造性分析：

1. **区别技术特征**：以D1为最接近的对比文件，目标专利权利要求1的区别技术特征主要在于：

* 特征I-N：确定并利用一个专门指示像素投影到3D地图上时由捕捉和虚拟观看视角差异导致的**几何失真**的**置信度值**，并基于此置信度值确定是否渲染或渲染组合（特别是特征L所描述的随距离淡出的动态效果）。

* 特征R：确定第一和第二射线之间的**角度**，且置信度是**基于该角度确定的**。

2. **创造性评价**：

* D2和D3并未公开上述区别技术特征。D2使用了深度信息进行层级渲染以解决视差错误，但并未定义一个基于捕捉视角和虚拟视角差异的角度来估计几何失真的置信度值。D3也仅涉及堆叠对齐。

* 目标专利的核心创造性在于提出一种**具体的失真估计方法**：利用原始相机射线（捕捉方向）和虚拟相机射线（观看方向）之间的**角度**来确定**置信度值**（特征R），并将该置信度值应用于像素淡入淡出的混合渲染中（特征L, M, N），以减轻由3D模型几何不精确导致的视觉伪影。在D1仅利用射线交点进行导航定向的基础上，结合角度计算置信度进行精细化像素混合，对于本领域技术人员来说，并非显而易见的技术组合或显而易见的技术发展方向。

#### 无效请求最薄弱的技术特征：

如果要提出无效请求，我认为目标专利中**最薄弱的技术特征**是：

**特征C：所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素；**

**薄弱理由分析：**

1. **D1的暗示**：虽然我将此特征判定为D1中无直接对应出处（因为D1使用了“虚拟模型”和“全景图像”而非标准的“三维地图”），但D1的整体架构（确定从全景图视口延伸的射线，确定该射线与表示物体立面的模型的交点）在逻辑上隐含了原始图像（全景图）的一个点与模型上的一个点之间的对应关系。

2. **特征组合的可能**：在D1公开了射线确定和相机位置确定的基础上，结合当时已有的成熟的 3D 地图渲染技术（本领域常识），将全景图像投影到成熟的3D地图模型上并找到几何对应的像素点，对于本领域技术人员来说，是显而易见的常识性技术手段的应用。

3. **对核心创造性的影响**：特征C仅描述了一个必要的对齐步骤，而非核心创造性所在（置信度估计和混合渲染）。如果能证明在提出目标专利申请之前，将全景图像像素与3D地图像素建立几何对应关系已经是本领域公知的对齐方法，那么特征C的贡献将微乎其微。

#### 结论总结：

目标专利的核心创造性特征在于**基于捕捉与虚拟相机射线之间角度确定的失真置信度值及其随距离减小的动态渲染机制**（由特征R、L、N组合构成）。如果提出无效请求，突破点可能在于特征C（像素几何对应），通过证明在3D地图渲染中将媒体像素投影并几何对应到地图像素是提出目标专利前本领域的公知常识，从而削弱目标专利的独特性，为进一步结合公知常识攻击创造性打下基础。但目前来看，该专利的核心特征仍具有较高的创造性高度。

根据权利要求1所述的方法，其中所述(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：对与所述至少一个已渲染的三维地图的至少一个用户交互的至少一个确定；以及至少部分地基于所述至少一个用户交互而对至少一个置信度值、所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染、或者它们的组合的动态更新。

根据权利要求2所述的方法，其中所述至少一个用户交互造成以下项的变化：(a)所述至少一个已渲染的三维地图的至少一个虚拟相机位置，(b)所述至少一个第一像素、所述至少一个图像、所述至少一个第二像素和所述至少一个已渲染的三维地图中的至少一个的至少一个渲染特性；或者(c)它们的组合；并且其中所述至少一个渲染特性至少部分地包括衰减参数、切换参数、大小参数，或者它们的组合。

根据权利要求1所述的方法，其中所述(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：所述至少一个置信度值与至少一个阈值置信度标准的比较，以确定是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的所述渲染。

根据权利要求1所述的方法，其中所述(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：对所述至少一个第一相机位置和所述至少一个第二相机位置之间的至少一个偏移量的至少一个确定，其中所述至少一个置信度值进一步至少部分地基于所述偏移量。

根据权利要求5所述的方法，其中(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：至少部分地基于所累加的置信度值对至少一个透明度水平的至少一个确定，所述至少一个透明度水平用于所述至少一个像素到所述至少一个已渲染的三维地图上的所述渲染。

根据权利要求6所述的方法，其中所述至少一个透明度水平随着所累加的置信度值的增大而减小。

根据权利要求1所述的方法，还包括： 参考所述第二相机位置而针对所述至少一个图像对至少一个深度偏移值的估计；以及利用至少一个估计的深度偏移值对深度偏移值缓冲器的迭代更新。

根据权利要求8所述的方法，其中所述至少一个图像到所述至少一个已渲染的三维地图上的所述渲染至少部分地基于所述至少一个深度偏移量值。

根据权利要求8所述的方法，其中所述至少一个图像到所述至少一个已渲染的三维地图上的所述渲染至少部分地基于所述至少一个用户交互和所述至少一个深度偏移量值。

根据权利要求8所述的方法，进一步包括： 参考所述第二相机位置而针对所述至少一个图像对至少一个新的候选深度偏移量值的生成； 至少部分地基于所述至少一个深度偏移量值的、至少一个测试图像到所述至少一个已渲染的三维地图上的第一渲染； 至少部分地基于所述至少一个新的候选深度偏移量值的、所述至少一个测试图像到所述至少一个已渲染的三维地图上的第二渲染；以及对所述第一渲染和所述第二渲染的分析，以确定与所述第一渲染和所述第二渲染相关联的一个或多个渲染特性。

根据权利要求11所述的方法，进一步包括： 至少部分地基于所述分析而利用所述至少一个深度偏移量值或所述至少一个新的候选深度偏移量值对所述深度偏移量值缓冲器的更新。

根据权利要求1所述的方法，其中所述(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：对所述至少一个图像包括多个重叠图像的至少一个确定；以及 至少部分地基于所述置信度值而对所述多个重叠图像的排序、混合或者它们的组合。

根据权利要求1-13中的任一项所述的方法，其中所述至少一个图像包括至少一个视频，并且其中所述(1)数据和/或(2)信息和/或(3)至少一个信号进一步至少部分地基于以下项：针对所述至少一个视频对至少一个三维运动轨迹的至少一个确定， 其中所述至少一个置信度值、所述至少一个像素到所述至少一个已渲染的三维地图上的所述渲染至少部分地基于所述至少一个三维运动轨迹。

一种用于处理数据的装置，包括： 至少一个处理器；和 包括用于一个或多个程序的计算机程序代码的至少一个存储器，所述至少一个存储器和所述计算机程序代码被配置为与所述至少一个处理器一起导致所述装置至少执行以下项：确定至少一个图像中的至少一个第一像素，所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素，其中所述至少一个第一像素和所述至少一个第二像素与相同的兴趣点相关； 处理以下项和/或促成对以下项的处理：(a)所述至少一个第一像素；(b)所述至少一个第二像素；(c)与所述至少一个第一像素和所述至少一个第二像素中的至少一个相关联的元数据；或者(d)它们的组合，以确定至少一个置信度值，其中所述至少一个置信度值指示所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平，所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致，其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小； 基于所述置信度值发起所述第一像素从所述虚拟观看视角到所述三维地图上的渲染； 以及 至少部分地基于所述置信度值确定是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染或者所述渲染的组合； 其中所述装置进一步被导致： 处理所述元数据和/或促成对所述元数据的处理，以确定与所述至少一个图像相关联的至少一个第一相机位置以及与所述至少一个已渲染的三维地图相关联的至少一个第二相机位置； 确定至少一个第一射线，所述至少一个第一射线从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置； 确定至少一个第二射线，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置；以及确定所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度，其中所述置信度值是至少部分地基于所述至少一个角度确定的。

根据权利要求15所述的装置，其中所述装置进一步被导致：确定与所述至少一个已渲染的三维地图的至少一个用户交互；以及 至少部分地基于所述至少一个用户交互而至少部分地导致对所述至少一个置信度值、所述至少一个第一像素到所述至少一个已渲染的三维地图上的所述渲染、或者它们的组合的动态更新。

根据权利要求16所述的装置，其中所述至少一个用户交互造成以下项的变化：(a)所述至少一个已渲染的三维地图的至少一个虚拟相机位置，(b)所述至少一个第一像素、所述至少一个图像、所述至少一个第二像素和所述至少一个已渲染的三维地图中的至少一个的至少一个渲染特性；或者(c)它们的组合；并且其中所述至少一个渲染特性至少部分地包括衰减参数、切换参数、大小参数、或者它们的组合。

根据权利要求15所述的装置，其中所述装置进一步被导致：至少部分地导致所述至少一个置信度值与至少一个阈值置信度标准的比较，以确定是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的所述渲染。

根据权利要求15所述的装置， 确定所述至少一个第一相机位置和所述至少一个第二相机位置之间的至少一个偏移量，其中所述至少一个置信度值进一步至少部分地基于所述偏移量。

根据权利要求15所述的装置，其中所述装置进一步被导致：至少部分地基于所累加的置信度值、针对所述至少一个像素到所述至少一个已渲染的三维地图上的所述渲染而确定至少一个透明度水平。

根据权利要求20所述的装置，其中所述至少一个透明度水平随着所累加的置信度值的增大而减小。

根据权利要求19所述的装置，其中所述装置进一步被导致：参考第二相机位置而至少部分地导致针对所述至少一个图像对至少一个深度偏移量值的估计；以及利用至少一个所估计的深度偏移量值而至少部分地导致对深度偏移量值缓冲器的迭代更新。

根据权利要求22所述的装置，其中所述至少一个图像到所述至少一个已渲染的三维地图上的渲染至少部分地基于至少一个深度偏移量值。

根据权利要求22所述的装置，其中所述至少一个图像到所述至少一个已渲染的三维地图上的所述渲染至少部分地基于所述至少一个用户交互和所述至少一个深度偏移量值。

根据权利要求22所述的装置，其中所述装置进一步被导致：参考所述第二相机位置而至少部分地导致针对所述至少一个图像对至少一个新的候选深度偏移量值的生成； 至少部分地基于所述至少一个深度偏移量值而至少部分地导致至少一个测试图像到所述至少一个已渲染的三维地图上的第一渲染； 至少部分地基于所述至少一个新的候选深度偏移量值而至少部分地导致所述至少一个测试图像到所述至少一个已渲染的三维地图上的第二渲染； 至少部分地导致对所述第一渲染和所述第二渲染的分析，以确定与所述第一渲染和所述第二渲染相关联的一个或多个渲染特性。

根据权利要求25所述的装置，其中所述装置进一步被导致：至少部分地基于所述分析而至少部分地导致利用所述至少一个深度偏移量值或所述至少一个新的候选深度偏移量值对所述深度偏移量值缓冲器的更新。

根据权利要求15所述的装置，其中所述装置进一步被导致：确定所述至少一个图像包括多个重叠图像；以及 至少部分地基于所述置信度值而至少部分地导致对所述多个重叠图像的排序、混合或者它们的组合。

根据权利要求15-27中的任一项所述的装置，其中所述至少一个图像包括至少一个视频，所述装置进一步被导致：针对所述至少一个视频确定至少一个三维运动轨迹， 其中所述至少一个置信度值、所述至少一个像素到所述至少一个已渲染的三维地图上的所述渲染至少部分地基于所述至少一个三维运动轨迹。

根据权利要求15所述的装置，其中所述装置是计算机系统，所述计算机系统包括一个或多个存储设备、一个或多个实时处理元件、一个或多个静态处理元件、或者它们的组合。

一种处理数据的方法，包括： 确定至少一个图像中的至少一个第一像素，所述至少一个第一像素几何对应于至少一个已渲染的三维地图的至少一个第二像素，其中所述至少一个第一像素和所述至少一个第二像素与相同的兴趣点相关； 处理以下项和/或促成对以下项的处理：(a)所述至少一个第一像素；(b)所述至少一个第二像素；(c)与所述至少一个第一像素和所述至少一个第二像素中的至少一个相关联的元数据；或者(d)它们的组合，以确定至少一个置信度值，其中所述至少一个置信度值指示所述第一像素中的每个像素当被投影到所述三维地图上时的几何失真的估计的水平，所述几何失真由与所述至少一个第一像素中的每个像素相关的所述图像的图像捕捉视角和所述三维地图的虚拟观看视角之间的差异所导致，其中相应的第一像素的所述置信度值随着所述虚拟观看视角远离所述图像捕捉视角而减小； 基于所述置信度值发起所述第一像素从所述虚拟观看视角到所述三维地图上的渲染； 以及 至少部分地基于所述置信度值确定是否至少部分导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的渲染或者所述渲染的组合； 所述方法进一步包括： 处理所述元数据和/或促成对所述元数据的处理，以确定与所述至少一个图像相关联的至少一个第一相机位置以及与所述至少一个已渲染的三维地图相关联的至少一个第二相机位置； 确定至少一个第一射线，所述从所述至少一个第一相机位置延伸到所述至少一个第一像素和所述至少一个第二像素中的至少一个的至少一个像素位置； 确定至少一个第二射线，所述至少一个第二射线从所述至少一个第二相机位置延伸到所述至少一个像素位置；以及确定所述至少一个第一射线和所述至少一个第二射线之间所形成的至少一个角度，其中所述置信度值是至少部分地基于所述至少一个角度确定的。

根据权利要求30所述的方法，进一步包括： 确定与所述至少一个已渲染的三维地图的至少一个用户交互；以及 至少部分地基于所述至少一个用户交互而至少部分地导致对所述至少一个置信度值、所述至少一个第一像素到所述至少一个已渲染的三维地图上的所述渲染、或者它们的组合的动态更新。

根据权利要求31所述的方法，其中所述至少一个用户交互造成以下项的变化：(a)至少一个已渲染的三维地图的至少一个虚拟相机位置，(b)所述至少一个第一像素、所述至少一个图像、所述至少一个第二像素和所述至少一个已渲染的三维地图中的至少一个的至少一个渲染特性；或者(c)它们的组合；并且其中所述至少一个渲染特性至少部分地包括衰减参数、切换参数、大小参数、或者它们的组合。

根据权利要求30-32中任一项所述的方法，进一步包括：导致所述至少一个置信度值与至少一个阈值置信度标准的比较，以确定是否至少部分地导致所述至少一个第一像素到所述至少一个已渲染的三维地图上的所述渲染。

根据权利要求30-32中任一项所述的方法，进一步包括：确定所述至少一个第一相机位置和所述至少一个第二相机位置之间的至少一个偏移量，其中所述至少一个置信度值进一步至少部分地基于所述偏移量。

根据权利要求34所述的方法，进一步包括： 至少部分地基于所累加的置信度值、针对所述至少一个像素到所述至少一个已渲染的三维地图的所述渲染而确定至少一个透明度水平。

根据权利要求35所述的方法，其中所述至少一个透明度水平随着所累加的置信度值的增大而减小。

根据权利要求34所述的方法，进一步包括： 至少部分地导致参考所述第二相机位置而针对至少一个图像对至少一个深度偏移量值的估计；以及至少部分地导致利用至少一个所估计的深度偏移量值对深度偏移量值缓冲器的迭代更新。

根据权利要求37所述的方法，其中所述至少一个图像到所述至少一个已渲染的三维地图上的所述渲染至少部分地基于所述至少一个深度偏移量值。

根据权利要求37和38中任一项所述的方法，其中所述至少一个图像到所述至少一个已渲染的三维地图上的所述渲染至少部分地基于所述至少一个用户交互和所述至少一个深度偏移量值。

根据权利要求37和38中任一项所述的方法，进一步包括：参考所述第二相机位置而至少部分地导致针对所述至少一个图像对至少一个新的候选深度偏移量值的生成； 至少部分地基于所述至少一个深度偏移量值而至少部分地导致所述至少一个测试图像到所述至少一个已渲染的三维地图上的第一渲染； 至少部分地基于至少一个新的候选深度偏移量值而至少部分地导致所述至少一个测试图像到所述至少一个已渲染的三维地图上的第二渲染； 至少部分地导致对所述第一渲染和所述第二渲染的分析，以确定与所述第一渲染和所述第二渲染相关联的一个或多个渲染特性。

根据权利要求40所述的方法，进一步包括： 至少部分地基于所述分析而至少部分地导致利用所述至少一个深度偏移量值或所述至少一个新的候选深度偏移量值对所述深度偏移量值缓冲器的更新。

根据权利要求30所述的方法，进一步包括： 确定所述至少一个图像包括多个重叠图像；以及 至少部分地基于所述置信度值而至少部分地导致对多个所述重叠图像的排序、混合或者它们的组合。

根据权利要求30所述的方法，其中所述至少一个图像包括至少一个视频，所述方法进一步包括：针对所述至少一个视频确定至少一个三维运动轨迹， 其中所述至少一个置信度值、所述至少一个像素到所述至少一个已渲染的三维地图上的所述渲染至少部分地基于所述至少一个三维运动轨迹。

一种计算机可读存储介质，其承载一个或多个指令的一个或多个序列，所述一个或多个指令的一个或多个序列在被一个或多个处理器执行时导致装置至少执行根据权利要求1-14和30-43中的任一项所述的方法。

一种用于处理数据的装置，包括用于至少执行根据权利要求1-14和30-43中的任一项所述的方法的部件。

根据权利要求45所述的装置，其中所述装置是移动设备，所述移动设备进一步包括：用户接口电路和用户接口软件，被配置为通过对显示器的使用而促成对所述移动设备的至少一些功能的用户控制并且被配置为对用户输入进行响应；以及显示器和显示电路，被配置为显示所述移动设备的用户接口的至少一部分，所述显示器和显示电路被配置为促成对所述移动设备的至少一些功能的用户控制。

一种计算机程序产品，包括一个或多个指令的一个或多个序列，所述一个或多个指令的一个或多个序列在被一个或多个处理器执行时导致装置至少执行根据权利要求1-14和30-43中的任一项所述的至少一种方法的步骤。

一种处理数据的方法，包括促成对至少一个接口的访问，所述接口被配置为允许对至少一项服务进行访问，所述至少一项服务被配置为至少执行根据权利要求1-14和30-43中的任一项所述的至少一种方法。

一种处理数据的方法，包括：促成对以下项的处理和/或处理以下项：(1)数据和/或(2)信息和/或(3)至少一个信号，所述(1)数据和/或(2)信息和/或(3)至少一个信号至少部分地基于根据权利要求1-14和30-43中的任一项所述的至少一种方法。

一种处理数据的方法，包括：促成创建和/或促成修改：(1)至少一个设备用户接口元件和/或(2)至少一个设备用户接口功能，所述(1)至少一个设备用户接口元件和/或(2)至少一个设备用户接口功能至少部分地基于根据权利要求1-14和30-43中的任一项所述的至少一种方法。