Robust Visual Tracking via Appearance Modeling and Sparse Representation

doi:10.4304/jcp.9.7.1612-1619

	Robust Visual Tracking via Appearance Modeling and Sparse Representation
	Li, Ming; Ma, Fanglan; Nian, Fuzhong
刊名	JOURNAL OF COMPUTERS
	2014-07-01
卷号	9 期号:7 页码:1612-1619
关键词	visual tracking appearance model sparse representation 2DPCA
ISSN号	1796-203X
DOI	10.4304/jcp.9.7.1612-1619
英文摘要	When appearance variation of object, partial occlusion or illumination change in object images occurs, most existing tracking approaches fail to track the target effectively. To deal with the problem, this paper proposed a robust visual tracking method based on appearance modeling and sparse representation. The proposed method exploits two-dimensional principal component analysis (2DPCA) with sparse representation theory for constructing appearance model. Then tracking is achieved by Bayesian inference framework, in which a particle filter is applied to evaluate the target state sequentially over time. In addition, to make the observation model more robust, the incremental learning algorithm is used to update the template set. Both qualitative and quantitative evaluations on four publicly available benchmark video sequences demonstrate that the proposed visual tracking algorithm performs better than several state-of-the-art algorithms.
WOS研究方向	Computer Science
语种	英语
出版者	ACAD PUBL
WOS记录号	WOS:000218222800016
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/155705]
专题	计算机与通信学院
作者单位	Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou, Gansu, Peoples R China
推荐引用方式 GB/T 7714	Li, Ming,Ma, Fanglan,Nian, Fuzhong. Robust Visual Tracking via Appearance Modeling and Sparse Representation[J]. JOURNAL OF COMPUTERS,2014,9(7):1612-1619.
APA	Li, Ming,Ma, Fanglan,&Nian, Fuzhong.(2014).Robust Visual Tracking via Appearance Modeling and Sparse Representation.JOURNAL OF COMPUTERS,9(7),1612-1619.
MLA	Li, Ming,et al."Robust Visual Tracking via Appearance Modeling and Sparse Representation".JOURNAL OF COMPUTERS 9.7(2014):1612-1619.