I'm currently using HOG (Histogram of Oriented Gradients) to generate feature vectors for each of my training images, and then using this data to train an SVM Classifier. Since the SVM classifies the incoming data into one of 2 classes, I understand I need to provide training images for both classes.
I hope to use this to detect pedestrians, and I have a set of a few hundred 128x64 images of different pedestrians. However, I'm not sure what images to use for the other class, i.e. the non-positive one. Should I just use images of different ambient scenes with no pedestrians in them?