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MDST-DGCN: A Multilevel Dynamic Spatiotemporal Directed Graph Convolutional Network for Pedestrian Trajectory Prediction

文献类型：期刊论文

作者Liu, Shaohua1; Liu, Haibo1; Wang, Yisu1; Sun, Jingkai1; Mao, Tianlu2
刊名COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
出版日期2022-04-12
卷号2022页码:10
ISSN号1687-5265
DOI10.1155/2022/4192367
英文摘要Pedestrian trajectory prediction is an essential but challenging task. Social interactions between pedestrians have an immense impact on trajectories. A better way to model social interactions generally achieves a more accurate trajectory prediction. To comprehensively model the interactions between pedestrians, we propose a multilevel dynamic spatiotemporal digraph convolutional network (MDST-DGCN). It consists of three parts: a motion encoder to capture the pedestrians' specific motion features, a multilevel dynamic spatiotemporal directed graph encoder (MDST-DGEN) to capture the social interaction features of multiple levels and adaptively fuse them, and a motion decoder to produce the future trajectories. Experimental results on public datasets demonstrate that our model achieves state-of-the-art results in both long-term and short-term predictions for both high-density and low-density crowds.
资助项目Major Program of the National Natural Science Foundation of China[91938301] ; National Natural Science Foundation of China[62002345]
WOS研究方向Mathematical & Computational Biology ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000791773700005
出版者HINDAWI LTD
源URL[http://119.78.100.204/handle/2XEOYT63/19538]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Mao, Tianlu
作者单位1.Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing 100876, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Shaohua,Liu, Haibo,Wang, Yisu,et al. MDST-DGCN: A Multilevel Dynamic Spatiotemporal Directed Graph Convolutional Network for Pedestrian Trajectory Prediction[J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE,2022,2022:10.
APA Liu, Shaohua,Liu, Haibo,Wang, Yisu,Sun, Jingkai,&Mao, Tianlu.(2022).MDST-DGCN: A Multilevel Dynamic Spatiotemporal Directed Graph Convolutional Network for Pedestrian Trajectory Prediction.COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE,2022,10.
MLA Liu, Shaohua,et al."MDST-DGCN: A Multilevel Dynamic Spatiotemporal Directed Graph Convolutional Network for Pedestrian Trajectory Prediction".COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022(2022):10.

入库方式： OAI收割

来源：计算技术研究所

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