Abstract
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.
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Conte, D., Foggia, P., Jolion, JM., Vento, M. (2005). A Graph-Based, Multi-resolution Algorithm for Tracking Objects in Presence of Occlusions. In: Brun, L., Vento, M. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2005. Lecture Notes in Computer Science, vol 3434. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31988-7_18
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DOI: https://doi.org/10.1007/978-3-540-31988-7_18
Publisher Name: Springer, Berlin, Heidelberg
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