Abstract
Vehicles on downtown roads can be occluded by other vehicles or by stationary scene components such as traffic lights or road signs. After having recorded such a scene by a video camera, we noticed that the occlusion may disturb the detection and tracking of vehicles by previous versions of our computer vision approach. In this contribution we demonstrate how our image sequence analysis system can be improved by an explicit model-based recognition of 3D occlusion situations. Results obtained from real world image sequences recording gas station traffic as well as inner-city intersection traffic are presented.KeywordsVehicle ModelTracking ProcessModel GradientScene ObjectAdvertising PostThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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