Pedestrian Detection and Analysis with Scale-Space and Distance Transform

Because the amount of various video streams recorded by video surveillance systems is increasing, the new approach, where human operator analyzing the video is replaced by artificial intelligence system is gaining new followers. The algorithm have to meet several requirements: must be accurate and not produce too many false alarms, moreover it must be able to process the received video stream in real-time to provide sufficient response time. In the article a system is presented which is able to detect and analyze walking pedestrians. It is based on two algorithms: scale space and matching contours using distance transform. The information can be used by other parts of the advanced video surveillance system, namely object tracking by detection, detecting heavy equipment only zone intrusion or for sorting out possible suspicious persons (pickpocket, homeless etc.).