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| Object Tacking with Particle Filter Based on Multi-Agent Co-Evolution |
| LI Yong-Ping, WANG Yan-Jiang, QI Yu-Juan |
| College of Information and Control Engineering, China University of Petroleum, Dongying 257061 |
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Abstract When tracking the moving targets in video image sequences, the existing particle filter is not satisfactory due to the particle degradation and particle diversity loss. An object tracking algorithm with particle filter is proposed. The multi-agent co-evolutionary mechanism is introduced into the particle resampling process and makes the particle become an agent with abilities of local perception, competitive selection and self-learning by redefining the particle agent and its local living environment. The resampling process is accomplished by the co-evolutionary behaviors among particles such as competition, crossover, mutation and self-learning. It ensures the particle validity and increases the particle diversity. Experimental results show that the proposed algorithm tracks the moving object accurately and robustly in complex video scenes.
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Received: 07 September 2009
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2011, Vol. 24 
