Due to the recent progress on autonomous driving, some technologies have been gradually deployed to the public transport vehicles. The passenger safety under the unmanned operating environment has become an emerging issue which requires much more attention. This paper presents a method for passenger detection, counting and action recognition inside a minibus. A top-view camera system is mounted on the ceiling to have a full coverage of the interior. 2D and 3D convolutional neural networks are developed for pose recognition and action classification of the passengers. The experiments are carried out in a self-driving minibus, and the results have demonstrated the feasibility of the proposed technique.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Passenger Detection, Counting, and Action Recognition for Self-Driving Public Transport Vehicles


    Beteiligte:
    Kao, Shih-Feng (Autor:in) / Lin, Huei-Yung (Autor:in)


    Erscheinungsdatum :

    2021-07-11


    Format / Umfang :

    2857271 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    PASSENGER DETECTION, COUNTING, AND ACTION RECOGNITION FOR SELF-DRIVING PUBLIC TRANSPORT VEHICLES

    Kao, Shih-Feng / Lin, Huei-Yung | British Library Conference Proceedings | 2021




    Review of Automatic Passenger Counting Systems in Public Urban Transport

    Grgurević, Ivan / Juršić, Karlo / Rajič, Vinko | Springer Verlag | 2021


    Counting public transport passenger using WiFi signatures of mobile devices

    Myrvoll, Tor A. / Hakegard, Jan E. / Matsui, Tomoko et al. | IEEE | 2017