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Progress and Outlook of Visual Tracking: Bibliographic Analysis and Perspective

文献类型：期刊论文

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作者Liu, Yating1,2; Wang, Kunfeng3; Li, Xuesong1,2; Bai, Tianxiang1,2; Wang, Fei-Yue1
刊名IEEE ACCESS ; IEEE ACCESS
出版日期2019 ; 2019
卷号7页码:184581-184598
关键词Visual tracking Visual tracking bibliographic analysis collaboration patterns research hotspots parallel vision bibliographic analysis collaboration patterns research hotspots parallel vision
ISSN号2169-3536 ; 2169-3536
DOI10.1109/ACCESS.2019.2959942 ; 10.1109/ACCESS.2019.2959942
通讯作者Wang, Kunfeng(wangkf@mail.buct.edu.cn) ; Wang, Kunfeng(wangkf@mail.buct.edu.cn)
英文摘要Benefitting from continuous progress in computer architecture and computer vision algorithms, the visual tracking field has earned its rapid development in recent years. This paper surveys this interesting field through bibliographic analysis on the Web-of-Science literature from 1990 to 2019. Specifically, statistical analysis methods are used to obtain the most productive authors and countries/regions, the most cited papers, and so on. In order to realize an in-depth analysis, the co-authors, co-keywords and keyword-author co-occurrence networks are built to intuitively exhibit the evolution of research hotspots and the collaboration patterns among world-wide researchers. Brief introductions of the topics that occur frequently in co-keywords networks are provided as well. Furthermore, existing challenges and future research directions within the visual tracking field are discussed, revealing that tracking-by-detection and deep learning will continue receiving much attention. In addition, the parallel vision approach should be adopted for training and evaluating visual tracking models in a virtual-real interaction manner.; Benefitting from continuous progress in computer architecture and computer vision algorithms, the visual tracking field has earned its rapid development in recent years. This paper surveys this interesting field through bibliographic analysis on the Web-of-Science literature from 1990 to 2019. Specifically, statistical analysis methods are used to obtain the most productive authors and countries/regions, the most cited papers, and so on. In order to realize an in-depth analysis, the co-authors, co-keywords and keyword-author co-occurrence networks are built to intuitively exhibit the evolution of research hotspots and the collaboration patterns among world-wide researchers. Brief introductions of the topics that occur frequently in co-keywords networks are provided as well. Furthermore, existing challenges and future research directions within the visual tracking field are discussed, revealing that tracking-by-detection and deep learning will continue receiving much attention. In addition, the parallel vision approach should be adopted for training and evaluating visual tracking models in a virtual-real interaction manner.
WOS关键词ROBUST OBJECT TRACKING ; ROBUST OBJECT TRACKING ; VISION ; MULTITARGET ; APPEARANCE ; MULTIVIEW ; IMAGES ; MODEL ; SET ; VISION ; MULTITARGET ; APPEARANCE ; MULTIVIEW ; IMAGES ; MODEL ; SET
资助项目National Key Research and Development Program of China[2018YFC1704400] ; National Key Research and Development Program of China[2018YFC1704400] ; National Natural Science Foundation of China[U1811463] ; National Natural Science Foundation of China[U1811463]
WOS研究方向Computer Science ; Computer Science ; Engineering ; Telecommunications ; Engineering ; Telecommunications
语种英语 ; 英语
WOS记录号WOS:000510021700012 ; WOS:000510021700012
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC ; IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/28608]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
通讯作者Wang, Kunfeng
作者单位1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Yating,Wang, Kunfeng,Li, Xuesong,et al. Progress and Outlook of Visual Tracking: Bibliographic Analysis and Perspective, Progress and Outlook of Visual Tracking: Bibliographic Analysis and Perspective[J]. IEEE ACCESS, IEEE ACCESS,2019, 2019,7, 7:184581-184598, 184581-184598.
APA Liu, Yating,Wang, Kunfeng,Li, Xuesong,Bai, Tianxiang,&Wang, Fei-Yue.(2019).Progress and Outlook of Visual Tracking: Bibliographic Analysis and Perspective.IEEE ACCESS,7,184581-184598.
MLA Liu, Yating,et al."Progress and Outlook of Visual Tracking: Bibliographic Analysis and Perspective".IEEE ACCESS 7(2019):184581-184598.

入库方式： OAI收割

来源：自动化研究所

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