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Vol. 173, Issue 6, June 2014, pp. 6-15




Development of Multi-target Tracking Technique Based on Background Modeling
and Particle Filtering

1, 2 Liao Xue-Chao, 3 Liu Zhen-Xing

1 School of Computer Science, Wuhan University of Science and Technology, Wuhan 430081, P. R. China
2 Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan 430081, P. R. China
3 School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, P. R. China
1 Tel.: +86-027-68893240, fax: +86-027-68893240

1 E-mail: liaoxuechao2008@sina.com


Received: 24 December 2013 /Accepted: 8 May 2014 /Published: 30 June 2014

Digital Sensors and Sensor Sysstems


Abstract: Based on implementing target tracking by means of particle filtering, a technique framework of tracking target by integrating particle filtering and background modeling is presented. The multi-target tracking (MTT) is classified into 5 modules as background modeling, multi-target tracking, initializing, re-initializing and particle filtering. Firstly, the author models each pixel of the image with Gaussian Mixture Model (GMM) to calculate the probability of background pixel in the current image so as to abstract foreground moving objects. Based on the background modeling, the algorithm flow and technique framework of generating the particle set of each object and particle filtering are presented. In the process of evaluating particle weight, in order to distinguish the different color features of the objects, the original algorithm (evaluating through Bhattacharyya distance) is improved. Only the color distribution of the foreground pixel in particle area after the background modeling is counted, therefore the accuracy and efficiency of target tracking are increased. The experiments prove that this algorithm can realize the effective tracking several moving persons.


Keywords: Particle filter, Multi-target tracking, Gaussian mixture model, Weight evaluation.


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