A 2D+t tensor voting based approach for tracking

Presents an approach to tracking objects in motion when observed by a fixed camera, with severe occlusions, merging/splitting objects and defects in the detection. We first detect regions corresponding to moving objects in each frame, then try to establish their trajectory. The method is based on a spatiotemporal (2D+t) representation of the moving regions, and uses the tensor voting methodology to enforce smoothness in space and time of the tracked regions. We demonstrate the performance of the system on several real sequences