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Occlusion handling approach in visual tracking based on multiple-kernel fusion
Xiao Peng1, Duan Miyi1, Zhao Qi2*
1. School of Computer Science and Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
2. Beijing Institute of Graphics, Beijing 100029, China

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Abstract�� A novel visual tracking approach based on multiple-kernel fusion was proposed to improve robustness and accuracy of tracking under large-area occlusion. Unlike traditional single symmetric kernel weighted histogram used in mean shift tracking, this approach adopted several asymmetric kernel functions centered at different positions within target region to build a set of asymmetric kernel weighted histograms. Because these histograms weighted each part of the target region differently, there must be some less influenced histograms during occlusion. Based on each histogram, a set of target location estimations were provided respectively by mean shift iteration, and the target location was obtained by fusing these estimations using Dempster-Shafer evidence theory. The experimental results demonstrate the effectiveness of the proposed approach under large-area occlusion.
Keywords�� target tracking   visual tracking   mean shift   occlusion handling   multiple kernels   evidence theory     
Received 2011-03-22;
Fund:������Ȼ��ѧ����������Ŀ(61005084)
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Ф��, �Λ���, ����.���ڶ���ںϵ�Ŀ�������ڵ�������[J]  �������պ����ѧѧ��, 2012,V38(6): 829-834,841
Xiao Peng, Duan Miyi, Zhao Qi.Occlusion handling approach in visual tracking based on multiple-kernel fusion[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2012,V38(6): 829-834,841
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