DocumentCode :
2814398
Title :
Multi-agent based particle filter for moving object tracking
Author :
Li, Yongping ; Wang, Yanjiang ; Qi, Yujuan ; Li, Hui
Author_Institution :
Coll. of Inf. & Control Eng., China Univ. of Pet., Dongying, China
Volume :
4
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
When tracking the moving targets in video image sequences with the existing particle filter, usually the tracking performance is not satisfactory due to the particle degradation and particle diversity loss. In this paper, we propose a novel particle filtering algorithm. In the algorithm, the multi-agent co-evolutionary mechanism is introduced into the particle re-sampling process and make the particle become an agent having ability of local perception, competitive selection and self-learning by the redefinition of particle agent and its local living environment. The re-sampling process is accomplished by the co-evolutionary behaviors among particles such as competition, crossover, mutation and self-learning, etc. It can not only ensure the particle validity but also increase the particle diversity. Experimental results show that the proposed algorithm can achieve better performance when tracking objects in complex video scenes.
Keywords :
image sequences; learning (artificial intelligence); multi-agent systems; object detection; particle filtering (numerical methods); moving object tracking; multiagent based particle filter; multiagent coevolutionary mechanism; particle resampling process; self learning; video image sequences; Computational modeling; Convergence; Lead; agent; co-evolution; object tracking; particle filter; re-sampling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5619310
Filename :
5619310
Link To Document :
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