Structure-Aware Local Sparse Coding for Visual Tracking

doi:10.1109/TIP.2018.2797482

	Structure-Aware Local Sparse Coding for Visual Tracking
	Qi, Yuankai 1; Qin, Lei 2; Zhang, Jian 3; Zhang, Shengping 4; Huang, Qingming 1,5; Yang, Ming-Hsuan 6
	2018-08-01
发表期刊	IEEE TRANSACTIONS ON IMAGE PROCESSING
ISSN	1057-7149
卷号	27 期号:8 页码:3857-3869
摘要	Sparse coding has been applied to visual tracking and related vision problems with demonstrated success in recent years. Existing tracking methods based on local sparse coding sample patches from a target candidate and sparsely encode these using a dictionary consisting of patches sampled from target template images. The discriminative strength of existing methods based on local sparse coding is limited as spatial structure constraints among the template patches are not exploited. To address this problem, we propose a structure-aware local sparse coding algorithm, which encodes a target candidate using templates with both global and local sparsity constraints. For robust tracking, we show the local regions of a candidate region should be encoded only with the corresponding local regions of the target templates that are the most similar from the global view. Thus, a more precise and discriminative sparse representation is obtained to account for appearance changes. To alleviate the issues with tracking drifts, we design an effective template update scheme. Extensive experiments on challenging image sequences demonstrate the effectiveness of the proposed algorithm against numerous state-of-the-art methods.
关键词	Visual tracking local sparse coding spatial structure information template update
DOI	10.1109/TIP.2018.2797482
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61620106009] ; National Natural Science Foundation of China[61332016] ; National Natural Science Foundation of China[U1636214] ; National Natural Science Foundation of China[61650202] ; National Natural Science Foundation of China[61572465] ; National Natural Science Foundation of China[61390510] ; National Natural Science Foundation of China[61732007] ; National Natural Science Foundation of China[61672188] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-SYS013] ; NSF[1149783]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000431451100002
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：54[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/5309
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Huang, Qingming
作者单位	1.Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Heilongjiang, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 3.King Abdullah Univ Sci & Technol, Visual Comp Ctr, Thuwal 239556900, Saudi Arabia 4.Harbin Inst Technol, Sch Comp Sci & Technol, Weihai 264209, Peoples R China 5.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China 6.Univ Calif Merced, Sch Engn, Merced, CA 95344 USA
推荐引用方式 GB/T 7714	Qi, Yuankai,Qin, Lei,Zhang, Jian,et al. Structure-Aware Local Sparse Coding for Visual Tracking[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2018,27(8):3857-3869.
APA	Qi, Yuankai,Qin, Lei,Zhang, Jian,Zhang, Shengping,Huang, Qingming,&Yang, Ming-Hsuan.(2018).Structure-Aware Local Sparse Coding for Visual Tracking.IEEE TRANSACTIONS ON IMAGE PROCESSING,27(8),3857-3869.
MLA	Qi, Yuankai,et al."Structure-Aware Local Sparse Coding for Visual Tracking".IEEE TRANSACTIONS ON IMAGE PROCESSING 27.8(2018):3857-3869.