According to the requirement of recognizing traffic police gestures for driver assistance systems and intelligent vehicles, a universal model for dynamic traffic police gesture recognition is firstly introduced, of which can accurately present the spatial context (such as the relative lengths of skeletons, the angles between each skeleton w. r. t. gravity, and part features) of the traffic police gestures. Secondly, an architecture which can respectively extract spatial context and temporal features of dynamic traffic police gesture is proposed. Meanwhile, deep neural network and LSTM are introduced to build a high-resolution traffic police gestures recognizer (namely HRTPGR). At last, the open Police Gesture Dataset is used to train and test TPGR, and the experimental results show that the TPGR achieves a state-of-the-art accuracy with 98.7% for dynamic traffic police gestures recognition, and has strong anti-interference ability to light, background and gesture shape changes.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A High-Resolution Approach for Dynamic Traffic Police Gestures Recognition Based on Spatial Context and Temporal Features Fusion


    Contributors:
    He, Jian (author) / Jiang, Shengsheng (author) / Wei, Xin (author) / Zhang, Cheng (author) / Dong, Ruihai (author)


    Publication date :

    2023-07-27


    Size :

    1520506 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English