Gesture recognition is an important step forward for both humans and machines but especially the interaction between them. The transport industry is a sector that can benefit greatly due to the reliance on using one’s hands to steer a car or cycle a bike. Bicycles often prove to be challenging regarding showing the intent of the cyclist to drivers, other cyclists and pedestrians. This paper showcases the development of a gesture recognition system that translates a cyclist’s gestures to better show their intentions to other road users through the use of an Arduino and LED. The solution uses the MediaPipe framework and a Convolutional Neural Network. It was trained and tested on using a custom dataset. There were four different classes of gestures (neutral, stop, direction and thanks) and provides a high degree of accuracy in recognition.


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    Titel :

    Gesture Recognition and Showing a Cyclist’s Intent


    Beteiligte:
    Bridgeman, Thomas (Autor:in) / Gibson, Helena (Autor:in) / Meehan, Kevin (Autor:in)


    Erscheinungsdatum :

    07.06.2023


    Format / Umfang :

    2728647 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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