With the increasing improvement of rail transit, the safety of railway traffic has received more and more attention, and efficient and accurate communication between train attendants is the basis of driving safety. Aiming at the gesture training of train attendants, this paper uses the MediaPipe module as the skeleton key point recognition framework on the basis of virtual reality technology, and designs a gesture recognition solution for train conductors by using skeleton information extraction technology and deep learning related methods. It can train train the conductor’s gestures, which has the characteristics of real-time, good interaction, initiative and flexibility.


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    Title :

    Motion Recognition System in VR Training System for Train Attendants


    Contributors:
    Yun, Chuan (author) / Su, Hu (author) / Han, Endong (author)


    Publication date :

    2023-05-12


    Size :

    773641 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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