object recognition using HOG features.
I am extracting HogFeatures to extract information from images. These numerical values i.e Hog features are used to train SVM for object classification. Is it the correct way to make a classifier for object recognition ? Also, how do I go about having the SVM trained.
Yes it is, there is a very nice example right here! Just do not forget to apply the HOG feature normalisation step before training an SVM.
@StevenPuttemans based on your experience, do you think it's so important to normalise HOG features?
@Lorena GdL I did not perform exhaustively testing on the SVM interface, but when I did, all the SVMs trained with that normalisation for pedestrian detection just outputted rubbish. That is when I found out about the normalisation and since then, my own models have been working. I guess it is necessary for OpenCV, not sure for other implementations. Maybe something in the internal optimization of the SVM that is influenced by this?