OpenCV中Latent SVM模型文件XML
2014-02-22 11:54
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原文:http://blog.csdn.net/loadstar_kun/article/details/8754359
从该blog开始,逐步介绍DPM + Latent SVM。关于OpenCV下DPM+Latent SVM简单介绍参考上一篇博文:OpenCV
Latent SVM Discriminatively Trained Part Based Models for Object Detection
以Cat.xml(opencv安装目录下sample/c内)为例
<Model>
<!-- Number of components -->
<NumComponents>2</NumComponents>
<!-- Number of features -->
<P>31</P>
<!-- Score threshold -->
<ScoreThreshold>-1.0028649999999999</ScoreThreshold>
<Component>
<!-- Root filterdescription -->
<RootFilter>
<!-- Dimensions-->
<sizeX>5</sizeX>
<sizeY>9</sizeY>
<!-- Weights(binary representation) -->
<Weights>
...
</Weights>
<!-- Linear termin score function -->
<LinearTerm>-2.2535784347835031</LinearTerm>
</RootFilter>
<!-- Part filtersdescription -->
<PartFilters>
<NumPartFilters>6</NumPartFilters>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
</PartFilters>
</Component>
<Component>
<!-- Root filterdescription -->
<RootFilter>
<!-- Dimensions-->
<sizeX>5</sizeX>
<sizeY>9</sizeY>
<!-- Weights(binary representation) -->
<Weights>
...
</Weights>
<!-- Linear termin score function -->
<LinearTerm>-2.5835343890077622</LinearTerm>
</RootFilter>
<!--Part filters description -->
<PartFilters>
<NumPartFilters>6</NumPartFilters>
<!-- Part filter? description -->
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
</PartFilters>
</Component>
</Model>
PartFilter内部结构:
<PartFilter>
<sizeX>6</sizeX>
<sizeY>6</sizeY>
<!-- Weights (binary representation)-->
<Weights></Weights>
<!-- Part filter offset -->
<V>
<Vx>3</Vx>
<Vy>1</Vy>
</V>
<!-- Quadratic penalty functioncoefficients -->
<Penalty>
<dx>0.0004031731821276</dx>
<dy>-0.0003745111759062</dy>
<dxx>0.0100010270581015</dxx>
<dyy>0.0205820897831230</dyy>
</Penalty>
</PartFilter>
注:1.里面的数据仅是为了说明,weight节点数据量太大,省略,PartFilter节点有点复杂,单列出来;
2.其中有些简洁说明性文字,不是很全,PartFilter中Vx,Vy为HOG的位移。Penalty节点下的各项是为了计算deformation
model。
从该blog开始,逐步介绍DPM + Latent SVM。关于OpenCV下DPM+Latent SVM简单介绍参考上一篇博文:OpenCV
Latent SVM Discriminatively Trained Part Based Models for Object Detection
以Cat.xml(opencv安装目录下sample/c内)为例
<Model>
<!-- Number of components -->
<NumComponents>2</NumComponents>
<!-- Number of features -->
<P>31</P>
<!-- Score threshold -->
<ScoreThreshold>-1.0028649999999999</ScoreThreshold>
<Component>
<!-- Root filterdescription -->
<RootFilter>
<!-- Dimensions-->
<sizeX>5</sizeX>
<sizeY>9</sizeY>
<!-- Weights(binary representation) -->
<Weights>
...
</Weights>
<!-- Linear termin score function -->
<LinearTerm>-2.2535784347835031</LinearTerm>
</RootFilter>
<!-- Part filtersdescription -->
<PartFilters>
<NumPartFilters>6</NumPartFilters>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
</PartFilters>
</Component>
<Component>
<!-- Root filterdescription -->
<RootFilter>
<!-- Dimensions-->
<sizeX>5</sizeX>
<sizeY>9</sizeY>
<!-- Weights(binary representation) -->
<Weights>
...
</Weights>
<!-- Linear termin score function -->
<LinearTerm>-2.5835343890077622</LinearTerm>
</RootFilter>
<!--Part filters description -->
<PartFilters>
<NumPartFilters>6</NumPartFilters>
<!-- Part filter? description -->
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
<PartFilter>...</PartFilter>
</PartFilters>
</Component>
</Model>
PartFilter内部结构:
<PartFilter>
<sizeX>6</sizeX>
<sizeY>6</sizeY>
<!-- Weights (binary representation)-->
<Weights></Weights>
<!-- Part filter offset -->
<V>
<Vx>3</Vx>
<Vy>1</Vy>
</V>
<!-- Quadratic penalty functioncoefficients -->
<Penalty>
<dx>0.0004031731821276</dx>
<dy>-0.0003745111759062</dy>
<dxx>0.0100010270581015</dxx>
<dyy>0.0205820897831230</dyy>
</Penalty>
</PartFilter>
注:1.里面的数据仅是为了说明,weight节点数据量太大,省略,PartFilter节点有点复杂,单列出来;
2.其中有些简洁说明性文字,不是很全,PartFilter中Vx,Vy为HOG的位移。Penalty节点下的各项是为了计算deformation
model。
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