Fall behavior recognition for old pedestrians based on kinematic characteristics

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

doi:10.1117/12.2662734

9 December 2022 Fall behavior recognition for old pedestrians based on kinematic characteristics

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

Proceedings Volume 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022); 1249210 (2022) https://doi.org/10.1117/12.2662734
Event: International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), 2022, Wuhan, China

Abstract

In public traffic scenarios, the old pedestrians, as the vulnerable and care-needing people, often have serious and irreversible effects on their bodies once accidents such as falls occur in their lives. To recognize the dangerous falling behavior of old pedestrians in public transportation buildings, this paper analyzes the gait frequency characteristics of the old pedestrians, tracks specific old pedestrians, adopts the kinematic stability theory, and obtains the kinematic characteristics of video image information based on computer vision technology. Finally, this study builds a kinematics model for the recognition of the fall behavior of the old pedestrians, which can provide an invisible safety guarantee for the safe travel of the old pedestrians.

Citation Download Citation

Zhu Wenjie, Zhao Rongyong, Zhang Hao, Jia Ping, Ma Yunlong, Li Cuiling, and Wang Yan "Fall behavior recognition for old pedestrians based on kinematic characteristics", Proc. SPIE 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), 1249210 (9 December 2022); https://doi.org/10.1117/12.2662734

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