Research Article | OPEN ACCESS
Study on Multi-Target Tracking Based on Particle Filter Algorithm
1, 2Junying Meng, 1Jiaomin Liu, 1Yongzheng Li and 1Juan Wang
1College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China
2Department of Computer Sciences, Shijiazhuang University, Shijiazhuang 050000, China
Research Journal of Applied Sciences, Engineering and Technology 2013 2:427-432
Received: May 04, 2012 | Accepted: June 08, 2012 | Published: January 11, 2013
Abstract
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.
Keywords:
Important sampling, MCMC, multi-target tracking, particle filter, sequential,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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