Efficient visual tracking using particle filter with incremental likelihood calculation
Information Sciences: an International Journal
Computers & Mathematics with Applications
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
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This paper presents a tracking-based surveillance system that is capable of tracking multiple moving objects, with almost real-time response, through the effective cooperation of multiple pan-tilt cameras. To construct this surveillance system, the distributed camera agent, which tracks multiple moving objects independently, is first developed. The particle filter is extended with target depth estimate to track multiple targets that may overlap with one another. A strategy to select the suboptimal camera action is then proposed for a camera mounted on a pan-tilt platform that has been assigned to track multiple targets within its limited field of view simultaneously. This strategy is based on the mutual information and the Monte Carlo method to maintain coverage of the tracked targets. Finally, for a surveillance system with a small number of active cameras to effectively monitor a wide space, this system is aimed to maximize the number of targets to be tracked. We further propose a hierarchical camera selection and task assignment strategy, known as the online position strategy, to integrate all of the distributed camera agents. The overall performance of the multicamera surveillance system has been verified with computer simulations and extensive experiments.