Spatial-Temporal Graph Network for Video Crowd Counting

doi:10.1109/TCSVT.2022.3187194

	Spatial-Temporal Graph Network for Video Crowd Counting
	Wu, Zhe 1; Zhang, Xinfeng 2; Tian, Geng 1; Wang, Yaowei 1; Huang, Qingming 1,2,3
	2023
发表期刊	IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
ISSN	1051-8215
卷号	33 期号:1 页码:228-241
摘要	In recent years, researchers have developed many deep-learning-based methods to count crowd numbers in static images. However, much fewer works focus on video-based crowd counting, in which the critical challenge of temporal correlation has not been well explored. This paper proposes a Spatial-Temporal Graph Network (STGN) to achieve efficient and accurate crowd counting in videos via learning pixel-wise and patch-wise relations in local spatial-temporal domains. Specifically, we design a pyramid graph module to leverage multi-scale features. In each scale, we sequentially construct three graphs: spatial-temporal pixel graph, temporal patch graph, and spatial pixel graph, in which we apply the self-attention mechanism to capture pixel-wise relation, learn structure-aware relation, and aggregate local features, respectively. Furthermore, we propose spatial-aware channel-wise attention to effectively fuse multi-scale features. To demonstrate the effectiveness of the proposed method, we conduct experiments on five crowd counting datasets, including a large-scale video crowd dataset (FDST). Moreover, the proposed model is also applied in the vehicle counting dataset (TRANCOS). The results show that the proposed model outperforms existing spatial-temporal crowd counting models and achieves state-of-the-art.
关键词	Computational modeling Predictive models Analytical models Long short term memory Optical flow Integrated circuit modeling Head Video-based crowd counting spatiotemporal graph attention multi-scale module
DOI	10.1109/TCSVT.2022.3187194
收录类别	SCI
语种	英语
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000911746000017
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：11[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/20033
专题	中国科学院计算技术研究所期刊论文
通讯作者	Wang, Yaowei
作者单位	1.Peng Cheng Lab, Shenzhen 518055, Peoples R China 2.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 101408, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Wu, Zhe,Zhang, Xinfeng,Tian, Geng,et al. Spatial-Temporal Graph Network for Video Crowd Counting[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2023,33(1):228-241.
APA	Wu, Zhe,Zhang, Xinfeng,Tian, Geng,Wang, Yaowei,&Huang, Qingming.(2023).Spatial-Temporal Graph Network for Video Crowd Counting.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,33(1),228-241.
MLA	Wu, Zhe,et al."Spatial-Temporal Graph Network for Video Crowd Counting".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 33.1(2023):228-241.