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Multi-Object Tracking With Spatial-Temporal Topology-Based Detector

文献类型：期刊论文

作者You, Sisi1; Yao, Hantao2; Xu, Changsheng2,3
刊名IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
出版日期2022-05-01
卷号32期号:5页码:3023-3035
ISSN号1051-8215
关键词Target tracking Topology Tracking Detectors Visualization Trajectory Proposals Multi-object tracking spatial-temporal topology-based detector spatial topology constraint temporal topology constraint
DOI10.1109/TCSVT.2021.3096237
通讯作者Xu, Changsheng(csxu@nlpr.ia.ac.cn)
英文摘要Multi-object tracking is a challenging task due to the occlusion of different targets. Existing methods focus on inferring a robust and discriminative feature for data association based on the targets generated by the existing detector. Unlike existing methods that consider each target independently during generating the trajectories, we propose a novel Spatial-Temporal Topology-based Detector (STTD) algorithm that treats the target and its nearest neighbors as a cluster and introduces a topology structure to describe the dynamics of moving targets belonging to the same cluster. With the public detections and the tracked objects in the previous frame, STTD firstly refines them by regression of detector to obtain the candidate proposals in the current frame. After that, the temporal topology constraint is proposed to recover the missed objects by considering the continuity and consistency of the topological structure. Based on the assumption that the targets belonging to the same topology should have a consistent characteristic, the spatial topology constraint is proposed to remove the inaccurate targets. Then we can obtain new candidate objects and construct the cost matrix used for data association. The evaluations on three MOTChallenge benchmarks verify the effectiveness of the proposed method.
WOS关键词ASSOCIATION ; MODEL
资助项目National Key Research and Development Program of China[2018AAA0102200] ; National Natural Science Foundation of China[61902399] ; National Natural Science Foundation of China[61721004] ; National Natural Science Foundation of China[U1836220] ; National Natural Science Foundation of China[U1705262] ; National Natural Science Foundation of China[61832002] ; National Natural Science Foundation of China[61720106006] ; National Natural Science Foundation of China[62072286] ; Beijing Natural Science Foundation[L201001] ; Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS)[QYZDJ-SSW-JSC039]
WOS研究方向Engineering
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000790830300044
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS)
源URL[http://ir.ia.ac.cn/handle/173211/48449]  
专题自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
通讯作者Xu, Changsheng
作者单位1.Hefei Univ Technol, Sch Comp Sci & Informat Engn, Hefei 230009, Peoples R China
2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 You, Sisi,Yao, Hantao,Xu, Changsheng. Multi-Object Tracking With Spatial-Temporal Topology-Based Detector[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2022,32(5):3023-3035.
APA You, Sisi,Yao, Hantao,&Xu, Changsheng.(2022).Multi-Object Tracking With Spatial-Temporal Topology-Based Detector.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,32(5),3023-3035.
MLA You, Sisi,et al."Multi-Object Tracking With Spatial-Temporal Topology-Based Detector".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 32.5(2022):3023-3035.

入库方式： OAI收割

来源：自动化研究所

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