Experiment study on pedestrian abnormal behavior detection and crowd stability analysis in cross passages

Cuiling Li; Rongyong Zhao; Yunlong Ma; Miyuan Li; Ping Jia; Wenjie Zhu; Yan Wang

doi:10.1117/12.2659989

9 December 2022 Experiment study on pedestrian abnormal behavior detection and crowd stability analysis in cross passages

Cuiling Li, Rongyong Zhao, Yunlong Ma, Miyuan Li, Ping Jia, Wenjie Zhu, Yan Wang

Author Affiliations +

Proceedings Volume 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022); 1249205 (2022) https://doi.org/10.1117/12.2659989
Event: International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), 2022, Wuhan, China

Abstract

Experiment design and implement to detect the possible pedestrian abnormal-behaviors in cross passages of public buildings are more significant to prevent possible crowd accidents than ever before. The further support of abnormal-behavior experiments can be helpful to stability analysis of moving pedestrian crowds. To summarize the experiments on pedestrian abnormal behavior detection based on computer vision technology, this study focuses both on the abnormal behaviors of moving pedestrians in public traffic areas and the computer vision technologies. A 3D scene analysis workflow using computer vision for crowd behavior experiment is designed. The Workflow model of abnormal behavior recognition and stability analysis in crowd movement used in experiment design is proposed based on Lyapunov criterion theory. Finally, a survey table of typical abnormal behaviors in public scenes is figured out.

Citation Download Citation

Cuiling Li, Rongyong Zhao, Yunlong Ma, Miyuan Li, Ping Jia, Wenjie Zhu, and Yan Wang "Experiment study on pedestrian abnormal behavior detection and crowd stability analysis in cross passages", Proc. SPIE 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), 1249205 (9 December 2022); https://doi.org/10.1117/12.2659989

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