Abstract | 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. | 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. | | | | | ISSN (Online): 2040-7467 ISSN (Print): 2040-7459 | | |