Volume 8 Number 5 (May 2013)
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JSW 2013 Vol.8(5): 1140-1144 ISSN: 1796-217X
doi: 10.4304/jsw.8.5.1140-1144

Target Tracking Based on Optimized Particle Filter Algorithm

Junying Meng1, 2, Jiaomin Liu1, Juan Wang1, Ming Han1

1College of Information Science and Engineering, Yanshan University, Qinhuangdao, China
2Department of Computer science, Shijiazhuang University, Shijiazhuang, China

AbstractParticle filter is a probability estimation method based on Bayesian framework and it has unique advantage to describe the target tracking non-linear and non-Gaussian. In this paper, Firstly, analyses the particle degeneracy and sample impoverishment in particle filter multi-target tracking algorithm, and secondly, it applies Markov Chain Monte Carlo (MCMC) method to improve re-sampling process and enhance performance of particle filter algorithm. Finally, the performance of the proposed method is certificated by experiment that tracking multiple targets of similar appearance and complex motion. The results show the efficacy of the proposed method in multi-target tracking.

Index TermsParticle filter; multi-target tracking; sequential important sampling; MCMC.


Cite: Junying Meng, Jiaomin Liu, Juan Wang, Ming Han, "Target Tracking Based on Optimized Particle Filter Algorithm," Journal of Software vol. 8, no. 5, pp. 1140-1144, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
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