Pedestrian Control at Intersections - Phase III

Abstract

This report presents a real-time system for pedestrian tracking in sequences of grayscale images acquired by a stationary CCD (charged-coupled devices) camera. The research objective involves integrating this system with a traffic control application, such as a pedestrian control scheme at intersections. The system outputs the spatiotemporal coordinates of each pedestrian during the period the pedestrian remains in the scene. The system processes at three levels: raw images, blobs, and pedestrians. It models blob tracking as a graph optimization problem and pedestrians as rectangular patches with a certain dynamic behavior. Kalman filtering is used to estimate pedestrian parameters. The system was implemented on a Datacube MaxVideo 20 equipped with a Datacube Max860 and on a Pentium-based PC. The system achieved a peak performance of more than 20 frames per second. Experimental results based on indoor and outdoor scenes demonstrated the system's robustness under many difficult situations such as partial or full occlusions of pedestrians.