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?
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
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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'.
For more information, visit the authors website. The page also contain the paper of this method.
来源：https://stackoverflow.com/questions/11832447/opencv-and-latent-svm-detector