CASIA OpenIR  > 复杂系统认知与决策实验室
Global Instance Tracking: Locating Target More Like Humans
Hu, Shiyu1,2; Zhao, Xin2,5; Huang, Lianghua2; Huang, Kaiqi2,3,4,5,6
Source PublicationIEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
ISSN0162-8828
2023
Volume45Issue:1Pages:576-592
Corresponding AuthorZhao, Xin(xzhao@nlpr.ia.ac.cn)
AbstractTarget tracking, the essential ability of the human visual system, has been simulated by computer vision tasks. However, existing trackers perform well in austere experimental environments but fail in challenges like occlusion and fast motion. The massive gap indicates that researches only measure tracking performance rather than intelligence. How to scientifically judge the intelligence level of trackers? Distinct from decision-making problems, lacking three requirements (a challenging task, a fair environment, and a scientific evaluation procedure) makes it strenuous to answer the question. In this article, we first propose the global instance tracking (GIT) task, which is supposed to search an arbitrary user-specified instance in a video without any assumptions about camera or motion consistency, to model the human visual tracking ability. Whereafter, we construct a high-quality and large-scale benchmark VideoCube to create a challenging environment. Finally, we design a scientific evaluation procedure using human capabilities as the baseline to judge tracking intelligence. Additionally, we provide an online platform with toolkit and an updated leaderboard. Although the experimental results indicate a definite gap between trackers and humans, we expect to take a step forward to generate authentic human-like trackers. The database, toolkit, evaluation server, and baseline results are available at http://videocube.aitestunion.com.
KeywordGlobal instance tracking single object tracking benchmark dataset performance evaluation human tracking ability
DOI10.1109/TPAMI.2022.3153312
WOS KeywordOBJECT TRACKING
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61721004] ; National Natural Science Foundation of China[61876181] ; Projects of Chinese Academy of Science[QYZDB-SSW-JSC006] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA27000000] ; Youth Innovation Promotion Association CAS
Funding OrganizationNational Natural Science Foundation of China ; Projects of Chinese Academy of Science ; Strategic Priority Research Program of Chinese Academy of Sciences ; Youth Innovation Promotion Association CAS
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000899419900035
PublisherIEEE COMPUTER SOC
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/51097
Collection复杂系统认知与决策实验室
Corresponding AuthorZhao, Xin
Affiliation1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Automat, Ctr Res Intelligent Syst & Engn, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Ctr Res Intelligent Syst & Engn, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Inst Automation, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
6.CAS Ctr Excellence Brain Sci & Intelligence Techno, Beijing 100190, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Hu, Shiyu,Zhao, Xin,Huang, Lianghua,et al. Global Instance Tracking: Locating Target More Like Humans[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2023,45(1):576-592.
APA Hu, Shiyu,Zhao, Xin,Huang, Lianghua,&Huang, Kaiqi.(2023).Global Instance Tracking: Locating Target More Like Humans.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,45(1),576-592.
MLA Hu, Shiyu,et al."Global Instance Tracking: Locating Target More Like Humans".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 45.1(2023):576-592.
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