Robust Structural Sparse Tracking

	Robust Structural Sparse Tracking
	Zhang, Tianzhu1,2 ; Xu, Changsheng1,2 ; Yang, Ming-Hsuan 3
发表期刊	IEEE Transactions on Pattern Analysis and Machine Intelligence
	2018-01
期号	pp 页码:1-1
摘要	Sparse representations have been applied to visual tracking by finding the best candidate region with minimal reconstruction error based on a set of target templates. However, most existing sparse trackers only consider holistic or local representations and do not make full use of the intrinsic structure among and inside target candidate regions, thereby making them less effective when similar objects appear at close proximity or under occlusion. In this paper, we propose a novel structural sparse representation, which not only exploits the intrinsic relationships among target candidate regions and local patches to learn their representations jointly, but also preserves the spatial structure among the local patches inside each target candidate region. For robust visual tracking, we take outliers resulting from occlusion and noise into account when searching for the best target region. Constructed within a Bayesian filtering framework, we show that the proposed algorithm accommodates most existing sparse trackers with respective merits. The formulated problem can be efficiently solved using an accelerated proximal gradient method that yields a sequence of closed form updates. Qualitative and quantitative evaluations on challenging benchmark datasets demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods.
关键词	Visual Tracking Sparse Tracking Structural Modeling Sparse Representation
WOS记录号	WOS:000456150600015
引用统计	被引频次：74[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/20470
专题	多模态人工智能系统全国重点实验室_多媒体计算
作者单位	1.National Lab of Pattern Recognition, Institute of Automation, CAS 2.University of Chinese Academy of Sciences 3.EECS, University of California at Merced, Merced, California United States 95344
推荐引用方式 GB/T 7714	Zhang, Tianzhu,Xu, Changsheng,Yang, Ming-Hsuan. Robust Structural Sparse Tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2018(pp):1-1.
APA	Zhang, Tianzhu,Xu, Changsheng,&Yang, Ming-Hsuan.(2018).Robust Structural Sparse Tracking.IEEE Transactions on Pattern Analysis and Machine Intelligence(pp),1-1.
MLA	Zhang, Tianzhu,et al."Robust Structural Sparse Tracking".IEEE Transactions on Pattern Analysis and Machine Intelligence .pp(2018):1-1.

条目包含的文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
pami17_rsst_final.pd（8609KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览