文章基本信息

标题：Visual Target Tracking Algorithm via Multi-scale Block and Sparse Representation
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作者：Ming Li ; Cui-Cui Kong ; Fu-Zhong Nian 等
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2015
卷号：8
期号：8
页码：333-344
DOI：10.14257/ijsip.2015.8.8.34
出版社：SERSC
摘要：In this paper, we propose a novel algorithm to deal with the problem of visual tracking in some challenging situations, which is based on sparse representation and multi-scale block. To build target templates, we select distinguishable features between the target and background in each frame of video sequences, dictionary is built by the multi-scale block of target templates. Then, particle filter generates filter distribution in the next frame, the moving target is framed by affine transformation. To describe the current state of the target, we calculate posterior probability for each particle. Finally, the templates are updated online. The experimental results show that the proposed algorithm is superior in accuracy than the classical tracking algorithm, and it has better robustness against to the target posture changes, partial occlusion and illumination variations
关键词：sparse representation; multi-scale block; template update; visual tracking