So, I've created my own HoG features extractor and a simple sliding window algorithm, which pseudo code looks like this:
for( int i = 0; i < img.rows; i++ ) {
for( int j = 0; j < img.cols; j++ ) {
extract image ROI from the current position
calculate features for the ROI
feed the features into svm.predict() function, to determine whether it's human or not
}
}
However since it's very slow (especially when you include different scales), I've decided to train some cascade classifiers using openv_traincascade command on my positive and negative samples.
opencv_traincascade provides me with cascade.xml, params.xml, and a number of stages.xml files
My question is how do I utilize this trained cascade classifiers in my detection loop ?