自适应分块的多特征融合多目标跟踪

doi:10.3969/j.issn.1001-2400.2017.02.026

Abstract

Abstract:

In order to solve the problems of occlusion, appearance change and similar targets in multi-target tracking, this paper proposes a multi-target tracking method with the particle filter based on the adaptive fragment and multi-feature fusion. First, we divide each target into a few fragments adaptively according to its gray projection and describe each fragment with the color histogram and histogram of oriented gradient(HOG) feature, of which similarity can be obtained by adopting the weighted Bhattacharyya Coefficient. Then, we obtain particle sets of each target by FCM clustering. The optimal state estimation of each target is calculated through particles state in the subgroup. Finally, the weighting factor of each fragment is updated according to the reliability which is calculated by considering particles space information. Experimental results show that the proposed method can track the targets in many complex circumstances accurately and robustly.

Key words: multiple targets, adaptive fragment, multi-feature fusion, histogram of oriented gradient, particle filter

BIE Xiude;LIU Hongbin;CHANG Faliang;PENG Zhiyong. Multi-target tracking method based on the adaptive fragment and multi-feature fusion[J].Journal of Xidian University, 2017, 44(2): 151-157.

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Multi-target tracking method based on the adaptive fragment and multi-feature fusion

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