A Low-Cost Pedestrian Detection System with a Single Optical Camera

This paper presents a low-cost solution for pedestrian detection using a single optical video camera on a moving vehicle. Since only one optical camera can collect just a little original information, our system scan two sequential frames to get both appearance and motion information. We use zoom image and slide window techniques to select the objective region, apply a cascaded classifier combined with statistical learning and SVM to recognize human body, adopt zoom-scale to estimate the distance from a pedestrian and develop a distance transform algorithm to forecast his/her orientation. This system is suitable for detecting pedestrians in the range of 0.3-20 meters in the city traffic with the speed under 50 km/h. The test with videos of real city traffic indicates that our system has got acceptable detecting rate and processing speed