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.


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    Titel :

    Fall behavior recognition for old pedestrians based on kinematic characteristics


    Beteiligte:
    Wenjie, Zhu (Autor:in) / Rongyong, Zhao (Autor:in) / Hao, Zhang (Autor:in) / Ping, Jia (Autor:in) / Yunlong, Ma (Autor:in) / Cuiling, Li (Autor:in) / Yan, Wang (Autor:in)

    Kongress:

    International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022) ; 2022 ; Wuhan,China


    Erschienen in:

    Proc. SPIE ; 12492


    Erscheinungsdatum :

    2022-12-09





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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