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Target modeling for tracking and handoff in a camera network

Tracking moving objects such as human has become a major topic in video surveillance applications. Camera handoff is an important problem when using multiple cameras which have overlapping or non-overlapping field of views. However, most handoff techniques rely on a robust tracker and some information from first camera assigned to tracked objects. In view-dependent appearance problem, a person might be seen simultaneously from different cameras but some variations such as differences in body posture, viewing angle, color characteristics, scale and lighting conditions may cause handoff failed from wrong object matching, multiple target models is needed. This paper presents a target modeling based on a CAMShift for moving object tracking. The target model process includes short-term and long-term memory. Experimental results have shown that our proposed algorithm can improve a person tracking among multiple PTZ cameras and especially solve the view-dependent appearance problem.