OpenCV和潜在SVM检测器 [英] OpenCV and Latent SVM Detector

问题描述

我想知道是否有人设法使用Latent SVM Detector的OpenCV实现( http://docs.opencv.org/modules/objdetect/doc/latent_svm.html )成功.有一个示例代码显示了如何利用该库，但问题是该示例代码使用了使用MatLab生成的现成的检测器模型.有人可以指导我完成如何生成自己的探测器模型的步骤吗?

I was wondering if anyone has managed to use the OpenCV implementation of Latent SVM Detector (http://docs.opencv.org/modules/objdetect/doc/latent_svm.html) successfully. There is a sample code that shows how to utilize the library but the problem is that the sample code uses a ready-made detector model that was generated using MatLab. Can some one guide me through the steps on how to generate my own detector model?

推荐答案

LatSVM 具有一个名为pascal的训练脚本.有一个自述文件，其中包含压缩包，说明了其用法:

The MATLAB implementation of LatSVM by the authors of the paper has a train script called pascal. There is a README with the tarball explaining its usage:

Using the learning code
=======================

1. Download and install the 2006-2011 PASCAL VOC devkit and dataset.
   (you should set VOCopts.testset='test' in VOCinit.m)
2. Modify 'voc_config.m' according to your configuration.
3. Start matlab.
4. Run the 'compile' function to compile the helper functions.
   (you may need to edit compile.m to use a different convolution 
    routine depending on your system)
5. Use the 'pascal' script to train and evaluate a model. 

example:
>> pascal('bicycle', 3);   % train and evaluate a 6 component bicycle model

The learning code saves a number of intermediate models in a model cache
directory defined in 'voc_config.m'.

有关更多信息，请访问作者网站.该页面还包含此方法的论文.

For more information, visit the authors website. The page also contain the paper of this method.

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