Knowledge Commons of Institute of Automation,CAS
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 |
ISSN | 0004-3702 |
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 |
DOI | 10.1016/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 | |
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. |
条目包含的文件 | 条目无相关文件。 |
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