Adaptive particle filter for object tracking based on fusing multiple features

被引：0
|
作者：
Yang, Xin [1 ,2 ,3 ]
Liu, Jia [1 ]
Zhou, Peng-Yu [1 ]
Zhou, Da-Ke [1 ]
机构：
[1] College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing
[2] School of Automation, Southeast University, Nanjing
[3] Key Laboratory of Photoelectric Control Technology, Luogyang
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2015年 / 45卷 / 02期
关键词：
Adaptive; Automatic control technology; Multi-feature fusion; Objects tracking; Particle filter;
D O I：
10.13229/j.cnki.jdxbgxb201502029
中图分类号：
学科分类号：
摘要：
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. ©, 2015, Editorial Board of Jilin University. All right reserved.
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收藏
页码：533 / 539
页数：6
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