A Graph-based, Multi-resolution Algorithm for Tracking Objects in Presence of Occlusions

In a video surveillance system the object tracking is one of the most challenging problem. In fact objects in the world exhibit complex interactions. When captured in a video sequence, some interactions manifest themselves as occlusions. A visual tracking system must be able to track objects which are partially or even fully occluded. In this paper we present a novel method of tracking objects through occlusions using a multi-resolution representation of the moving regions. The matching between objects in two consecutive frames to recognize the trajectories is preformed in a graph theoretic approach. The experimental results on the standard database PEST2001 show that the approach looks promising.