Hi, im doing a project where I am classifying foreground and background elements using HOG features and SVM ,
I have a sliding window that goes over an image and extracts hog features, it compares each result to a ground truth image and stores the foreground and background in the correct array.

as the background is a lot larger i am currently taking the first x amount from background to match up with the foreground to make it even.

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is this a good idea or should i run it with all the background data and make it unbalanced, or even more so, is it ok to keep repeating the foreground to match the background (i think this is a very bad / pointless idea)

Thanks in advance.