吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (2): 533-539.doi: 10.13229/j.cnki.jdxbgxb201502029

• Orignal Article • Previous Articles     Next Articles

Adaptive particle filter for object tracking based on fusing multiple features

YANG Xin1,2,3,LIU Jia1,ZHOU Peng-yu1,ZHOU Da-ke1   

  1. 1.College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016,China;
    2.School of Automation, Southeast University, Nanjing 210096,China;
    3.Key Laboratory of Photoelectric Control Technology,Luogyang 471000,China
  • Received:2013-07-01 Online:2015-04-01 Published:2015-04-01

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Abstract: In target tracking using a single feature, the tracking robustness can not be guaranteed in the case of complex environments, and the increase in particle number will lead to in low efficiency of the algorithm. To overcome these problems, a multiple feature fusion strategy is chosen to ensure sustained and stable tracking. Using this strategy, the weights of features will be adjusted adaptively to the environmental changes, and the number of particles is adaptive to improve the efficiency of the algorithm. Experimental results show that the proposed algorithm can effectively solve the target rotation, target occlusion, background confusion and many other issues with high robustness.

Key words: automatic control technology, objects tracking, particle filter, multi-feature fusion, adaptive

CLC Number: 

  • TP29
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