A Novel Method For Tracking And Counting Pedestrians In Real-Time Using A Single
نویسندگان
چکیده
This paper presents a real-time system for pedestrian tracking in sequences of grayscale images acquired by a stationary CCD camera. The objective is to integrate this system with a traffic control application such as a pedestrian control scheme at intersections. The proposed approach can also be used to detect and track humans in front of vehicles. Furthermore, the proposed schemes can 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 Datacube MaxVideo 20 equipped with a Datacube Max860 and was able to achieve a peak performance of over 30 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. This work has been supported by the Minnesota Department of Transportation through Contracts #71789-72983-169 and #71789-72447-159, the Center for Transportation Studies through Contract #USDOT/DTRS 93-G-0017-01, the National Science Foundation through Contracts #IRI-9410003 and #IRI-9502245, the Department of Energy (Sandia National Laboratories) through Contracts #AC-3752D and #AL-3021, and the McKnight Land-Grant Professorship Program at the University of Minnesota. O. Masoud and N.P. Papanikolopoulos are with the Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455; email: [email protected] , [email protected]. A Novel Method For Tracking And Counting Pedestrians In Real-Time Using A Single Osama Masoud, Nikolaos P. Papanikolopoulos
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