Knowledge Commons of Institute of Automation,CAS
SegDQ: Segmentation assisted multi-object tracking with dynamic query-based transformers | |
Liu, Yating1,2; Bai, Tianxiang1,2; Tian, Yonglin3; Wang, Yutong1; Wang, Jiangong1,2; Wang, Xiao1,4; Wang, Fei-Yue1 | |
发表期刊 | NEUROCOMPUTING |
ISSN | 0925-2312 |
2022-04-07 | |
卷号 | 481页码:91-101 |
摘要 | Multi-Object Tracking (MOT) has been one of the most important topics in computer vision. The tradi-tional tracking-by-detection framework of MOT is severely suffered from the poor detection results. In this paper, based on Transformer, we introduce the tracking-by-query MOT framework, and propose to apply semantic segmentation as an auxiliary task to optimize the training of MOT trackers, which addresses more on extracted foreground features. In addition, a feature-dependent dynamic object query (DOQ), instead of a fixed-learned object query (LOQ), is put forward to retrieve the new detections, improving the flexibility and constringency of the framework. We tested our SegDQ method on various scenarios including MOTChallenge 15, 16 and 17 datasets. The experimental results show that it obvi-ously improves the MOTA and IDF1 indexes of tracking results. (c) 2022 Published by Elsevier B.V. |
关键词 | Multi-object tracking Transformer Semantic task Dynamic query |
DOI | 10.1016/j.neucom.2022.01.073 |
关键词[WOS] | ONLINE TRACKING |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[62173329] ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles (ICRI-IACV) |
项目资助者 | National Natural Science Foundation of China ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles (ICRI-IACV) |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000761785300009 |
出版者 | ELSEVIER |
七大方向——子方向分类 | 目标检测、跟踪与识别 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48036 |
专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 |
通讯作者 | Wang, Fei-Yue |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Univ Sci & Technol China, Dept Automat, Hefei 230027, Peoples R China 4.Qingdao Acad Intelligent Ind, Qingdao 266000, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Liu, Yating,Bai, Tianxiang,Tian, Yonglin,et al. SegDQ: Segmentation assisted multi-object tracking with dynamic query-based transformers[J]. NEUROCOMPUTING,2022,481:91-101. |
APA | Liu, Yating.,Bai, Tianxiang.,Tian, Yonglin.,Wang, Yutong.,Wang, Jiangong.,...&Wang, Fei-Yue.(2022).SegDQ: Segmentation assisted multi-object tracking with dynamic query-based transformers.NEUROCOMPUTING,481,91-101. |
MLA | Liu, Yating,et al."SegDQ: Segmentation assisted multi-object tracking with dynamic query-based transformers".NEUROCOMPUTING 481(2022):91-101. |
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