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You have a set of background images, which you input when running the training algorithm, and they're used as negative images. However these images are not use as they are, i. e. a full complete image is not taken. Instead, the algorithm chooses windows of these images, of the appropriate size (the size of the positive images). That means that a single background image will be used as many negative smaller images (supposing it's bigger than positive samples, what it's normally true). So, the -numNeg parameters indicates the number of windows taken, and not the number of real input background images
