CASIA OpenIR  > 智能系统与工程
Multiple object tracking: A literature review
Luo, Wenhan1,2; Xing, Junliang3,6; Milan, Anton4; Zhang, Xiaoqin5; Liu, Wei1; Kim, Tae-Kyun2
发表期刊ARTIFICIAL INTELLIGENCE
ISSN0004-3702
2021-04-01
卷号293页码:23
通讯作者Xing, Junliang(jlxing@nlpr.ia.ac.cn)
摘要Multiple Object Tracking (MOT) has gained increasing attention due to its academic and commercial potential. Although different approaches have been proposed to tackle this problem, it still remains challenging due to factors like abrupt appearance changes and severe object occlusions. In this work, we contribute the first comprehensive and most recent review on this problem. We inspect the recent advances in various aspects and propose some interesting directions for future research. To the best of our knowledge, there has not been any extensive review on this topic in the community. We endeavor to provide a thorough review on the development of this problem in recent decades. The main contributions of this review are fourfold: 1) Key aspects in an MOT system, including formulation, categorization, key principles, evaluation of MOT are discussed; 2) Instead of enumerating individual works, we discuss existing approaches according to various aspects, in each of which methods are divided into different groups and each group is discussed in detail for the principles, advances and drawbacks; 3) We examine experiments of existing publications and summarize results on popular datasets to provide quantitative and comprehensive comparisons. By analyzing the results from different perspectives, we have verified some basic agreements in the field; and 4) We provide a discussion about issues of MOT research, as well as some interesting directions which will become potential research effort in the future. (C) 2021 Elsevier B.V. All rights reserved.
关键词Multi-object tracking Data association Survey
DOI10.1016/j.artint.2020.103448
关键词[WOS]MULTITARGET TRACKING ; MULTIOBJECT TRACKING ; ASSOCIATION ; MODEL
收录类别SCI
语种英语
资助项目National Key Research and Development Program of China[2019AAA010340X] ; Natural Science Foundation of China[62076238] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA27000000]
项目资助者National Key Research and Development Program of China ; Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Sciences
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000621632800004
出版者ELSEVIER
七大方向——子方向分类图像视频处理与分析
引用统计
被引频次:252[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/43315
专题智能系统与工程
通讯作者Xing, Junliang
作者单位1.Tencent AI Lab, Shenzhen, Peoples R China
2.Imperial Coll London, London, England
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
4.Amazon Res & Dev Ctr, Berlin, Germany
5.Wenzhou Univ, Wenzhou, Peoples R China
6.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
通讯作者单位模式识别国家重点实验室
推荐引用方式
GB/T 7714
Luo, Wenhan,Xing, Junliang,Milan, Anton,et al. Multiple object tracking: A literature review[J]. ARTIFICIAL INTELLIGENCE,2021,293:23.
APA Luo, Wenhan,Xing, Junliang,Milan, Anton,Zhang, Xiaoqin,Liu, Wei,&Kim, Tae-Kyun.(2021).Multiple object tracking: A literature review.ARTIFICIAL INTELLIGENCE,293,23.
MLA Luo, Wenhan,et al."Multiple object tracking: A literature review".ARTIFICIAL INTELLIGENCE 293(2021):23.
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