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Abstract
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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
Submitted: May 04, 2012
Accepted: June 08, 2012
Published: January 11, 2013 |
Abstract:
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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.
Key words: Important sampling, MCMC, multi-target tracking, particle filter, sequential, ,
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Abstract
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Cite this Reference:
Junying Meng, Jiaomin Liu, Yongzheng Li and Juan Wang, . Study on Multi-Target Tracking Based on Particle Filter Algorithm. Research Journal of Applied Sciences, Engineering and Technology, (02): 427-432.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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