Fast human detection using template matching for gradient images and aSC descriptors based on subtraction stereo

A fast human detection system using a stereo camera is constructed. “Subtraction stereo”, that can measure distance information of foreground regions, is used to restrict regions for human detection and to adapt the detection window size. Two methods are introduced for human detection. One is a method based on template matching using gradient images, and the other is a method using approximated Shape Context (aSC) descriptors focusing on human upper bodies. High human detection performance better than the standard HOG-based method with low calculation cost is achieved by the combination of the two methods. The effectiveness of the proposed system is verified experimentally.