Robust visual tracking of infrared object via sparse representation model
文献类型：会议论文
| 作者 | Ma JK(马俊凯); Luo HB(罗海波) ; Chang Z(常铮); Hui B(惠斌)
|
| 出版日期 | 2014 |
| 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 |
| 关键词 | Sparse representation Target tracking Appearance model Robust tracking Particle lter |
| 页码 | 1-6 |
| 中文摘要 | 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. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | Proc. Of SPIE 9301, International Symposium on Optoelectronic Technology and Application
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| 会议录出版者 | SPIE |
| 会议录出版地 | Bellingham, WA |
| 语种 | 英语 |
| ISSN号 | 0277-786X |
| WOS记录号 | WOS:000349327100100 |
| 源URL | [http://ir.sia.cn/handle/173321/15334]  |
| 专题 | 沈阳自动化研究所_光电信息技术研究室 |
| 推荐引用方式 GB/T 7714 | Ma JK,Luo HB,Chang Z,et al. Robust visual tracking of infrared object via sparse representation model[C]. 见:International Symposium on Optoelectronic Technology and Application 2014. Beijing, China. May 13-15, 2014. |
入库方式： OAI收割
来源：沈阳自动化研究所
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