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I'm currently working with HoG and SVM too and found this turorial:

It uses external SVM (SVM light) for training and loads the trained vector back to openCV HoG detector.

As far as I understand, you would have to subsample the INRIA images, so take the center pixels (64 x 128) of the positive sample images and use like 10 subimages (64 x 128) from each negative sample image.

After training you might want to detect (multiscale) in each negative sample image and add all detected persons to the negative sample list (scale to 64 x 128 if necessary) and re-train (since there are in fact no persons in the negative sample images)