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Vol. 161, Issue 12, December 2013, pp. 135-141




Object Tracking Based on Multi-Bernoulli Filter and Improved Nearest Neighbor Algorithm
Zhe CHEN, Huibin WANG, Jie SHEN, Jinyu BAO

College of Computer and Information Engineering, Hohai University, Nanjing, 210098, China
E-mail: hbwang@hhu.edu.cn


Received: 9 October 2013   /Accepted: 22 November 2013   /Published: 30 December 2013

Digital Sensors and Sensor Sysstems


Abstract: Generally, the multi-Bernoulli filter does not have robust ability to generate the motion trajectory. To solve this problem, in this paper, the improved nearest neighbor algorithm is introduced and combined with the multi-Bernoulli filter for multi-object tracking. The observation likelihood is obtained by statistical analysis on the distribution of the image pixels. Then, the amount of the objects and their location are predicted, extracted and updated by combining the spatial information and the color statistical model. As the result, the proposed method solves the problem that the traditional nearest neighbor algorithm cannot accurately correlate the objects if object increases. The experimental results demonstrate that the proposed method has super performance in multi-object tracking and trajectory correlation.


Keywords: Multi-Bernoulli filter, Nearest neighbor algorithm, Trajectory correlation, Random finite set.


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