ihi P APTI 3 0314 0028 2839 Repon 2000 - 28 V Pedestrian Control At Intersections : Phase IV

This report presents a real-time system for pedestrian tracking in sequences of grayscale images acquired by a stationary camera. Researchers also developed techniques for recognizing pedestrian's actions, such as running and walking, and integrated the system with a pedestrian control scheme at intersections. The proposed approach can be used to detect and track humans in a variety of applications. Furthermore, the proposed schemes also can be employed for the detection of several diverse traffic objects of interest, such as vehicles or bicycles. The system outputs the spatio-temporal coordinates of each pedestrian during the period the pedestrian is in the scene. The system processes at three levels: raw images, blobs and pedestrians. 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. In particular, this report contains the results from a field test of the system conducted in November 1999. The contents of this report reflect the views of the authors who are responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect the views or policies of the Minnesota Department of Transportation at the time of publication. This report does not constitute a standard, specification, or regulation. The authors and the Minnesota Department of Transportation do not endorse products or manufacturers. Trade or manufacturers' names appear herein solely because they are considered essential to this report. Executive Summary This report presents a real-time system for pedestrian tracking in sequences of grayscale images acquired by a stationary camera. We have also developed techniques for recognizing pedestrian's actions (e.g., running, walking, etc.). We have integrated the system with a pedestrian control scheme at intersections. The proposed approach can be used to detect and track humans in a variety of applications. Furthermore, the proposed schemes can also be employed for the detection of several diverse traffic objects of interest (vehicles, bicycles , etc.) The system outputs the spatio-temporal coordinates of each pedestrian during the period the pedestrian is in the scene. Processing is done at three levels: raw images, blobs, and pedestrians. Blob tracking is modeled as a graph optimization problem. Pedestrians are modeled as rectangular patches with a certain dynamic behavior. Kalman filtering is used to estimate pedestrian parameters. The system was implemented on a PC equipped with a Matrox Genesis board and was able to achieve a peak performance of …