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2013 (Vol. 5, Issue: 02)
Article Information:

Study on Multi-Target Tracking Based on Particle Filter Algorithm

Junying Meng, Jiaomin Liu, Yongzheng Li and Juan Wang
Corresponding Author:  Junying Meng 

Key words:  Important sampling, MCMC, multi-target tracking, particle filter, sequential, ,
Vol. 5 , (02): 427-432
Submitted Accepted Published
May 04, 2012 June 08, 2012 January 11, 2013

Particle 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 study, 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.
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  Cite this Reference:
Junying Meng, Jiaomin Liu, Yongzheng Li and Juan Wang, 2013. Study on Multi-Target Tracking Based on Particle Filter Algorithm.  Research Journal of Applied Sciences, Engineering and Technology, 5(02): 427-432.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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