1 June 1996 Model-based vehicle tracking from image sequences with an application to road surveillance
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Abstract
A model-based approach to vehicle tracking is proposed and applied to a highway traffic surveillance problem, which is motivated by current research in intelligent transportation systems. Systems for traffic management and traveler information services require accurate and wide-area estimates of vehicle velocity and traffic spatial and temporal densities. A detection and tracking algorithm is developed that achieves good performance with complexity low enough for real-time implementation using inexpensive microprocessors. Detection thresholds are computed based on a statistical model for vehicle and background, and the theoretical detector performance is derived. The tracking algorithm filters position estimates from the detection algorithm using a simple vehicle dynamic model and the Kalman filter. Data association is accomplished with a nearest neighbor filter coupled with a lane-change handling logic.
Wai Ying Kan, Wai Ying Kan, James V. Krogmeier, James V. Krogmeier, Peter C. Doerschuk, Peter C. Doerschuk, } "Model-based vehicle tracking from image sequences with an application to road surveillance," Optical Engineering 35(6), (1 June 1996). https://doi.org/10.1117/1.600747 . Submission:
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