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题名: Robust visual tracking of infrared object via sparse representation model
作者: Ma JK(马俊凯) ; Luo HB(罗海波) ; Chang Z(常铮) ; Hui B(惠斌)
作者部门: 光电信息技术研究室
会议名称: International Symposium on Optoelectronic Technology and Application 2014
会议日期: May 13-15, 2014
会议地点: Beijing, China
会议录: Proc. Of SPIE 9301, International Symposium on Optoelectronic Technology and Application
会议录出版者: SPIE
会议录出版地: Bellingham, WA
出版日期: 2014
页码: 1-6
收录类别: CPCI(ISTP) ; EI
ISSN号: 0277-786X
关键词: Sparse representation ; Target tracking ; Appearance model ; Robust tracking ; Particle lter
摘要: In this paper, we propose a robust tracking method for infrared object. We introduce the appearance model and the sparse representation in the framework of particle filter to achieve this goal. Representing every candidate image patch as a linear combination of bases in the subspace which is spanned by the target templates is the mechanism behind this method. The natural property, that if the candidate image patch is the target so the coefficient vector must be sparse, can ensure our algorithm successfully. Firstly, the target must be indicated manually in the first frame of the video, then construct the dictionary using the appearance model of the target templates. Secondly, the candidate image patches are selected in following frames and the sparse coefficient vectors of them are calculated via `1-norm minimization algorithm. According to the sparse coefficient vectors the right candidates is determined as the target. Finally, the target templates update dynamically to cope with appearance change in the tracking process. This paper also addresses the problem of scale changing and the rotation of the target occurring in tracking. Theoretic analysis and experimental results show that the proposed algorithm is elective and robust.
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/15334
Appears in Collections:光电信息技术研究室_会议论文

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