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Structure-Aware Local Sparse Coding for Visual Tracking

文献类型：期刊论文

作者Qi, Yuankai2; Qin, Lei3; Zhang, Jian4; Zhang, Shengping5; Huang, Qingming1,2; Yang, Ming-Hsuan6
刊名IEEE TRANSACTIONS ON IMAGE PROCESSING
出版日期2018-08-01
卷号27期号:8页码:3857-3869
ISSN号1057-7149
关键词Visual tracking local sparse coding spatial structure information template update
DOI10.1109/TIP.2018.2797482
英文摘要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.
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
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000431451100002
源URL[http://119.78.100.204/handle/2XEOYT63/5308]  
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.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China
2.Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Heilongjiang, Peoples R China
3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
4.King Abdullah Univ Sci & Technol, Visual Comp Ctr, Thuwal 239556900, Saudi Arabia
5.Harbin Inst Technol, Sch Comp Sci & Technol, Weihai 264209, 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.

入库方式： OAI收割

来源：计算技术研究所

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