For the autonomous driving system, accurately recognizing the actions of different roles in the traffic scene is the prerequisite for realizing this kind of human-vehicle information interaction. In this paper, we propose a complete framework based on 3D human pose estimation to recognize the actions of different roles on the road. The main objects recognized include traffic police, cyclists, and some passersby in need. We perform action recognition based on a dynamic adaptive graph convolutional network, which can realize the action recognition of objects based on 3D human pose. In addition to the action recognition module, we have optimized both the object detection module and the human pose estimation module in the framework so that the framework can handle multiple objects at the same time, which can be closer to the real traffic scene. To realize complex and changeable human action recognition, we built a multi-view camera system to collect responsible 3D human pose datasets containing traffic police gestures, cyclist gestures, and pedestrians’ body movements. In the experiments, compared to other state-of-the-art researches, the proposed framework can achieve comparable results with the same dataset. Satisfactory performance has also been obtained on the real data we collected, which can handle a variety of different action recognition tasks at the same time.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Action Recognition Framework in Traffic Scene for Autonomous Driving System


    Contributors:
    Xu, Feiyi (author) / Xu, Feng (author) / Xie, Jiucheng (author) / Pun, Chi-Man (author) / Lu, Huimin (author) / Gao, Hao (author)

    Published in:

    Publication date :

    2022-11-01


    Size :

    2926652 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Scene recognition in autonomous driving environment

    YLENHAMMAR MAGNUS / SVEINKRONA HU KAN | European Patent Office | 2022

    Free access

    AUTONOMOUS DRIVING METHOD AND SYSTEM BASED ON SCENE ADAPTIVE RECOGNITION

    HUANG LEXIONG / WANG SHUAI / HAN RUIHUA et al. | European Patent Office | 2024

    Free access


    FUSION-BASED TRAFFIC LIGHT RECOGNITION FOR AUTONOMOUS DRIVING

    WANG FAN / CHAI HUAJUN / HUANG KE et al. | European Patent Office | 2020

    Free access

    Fusion-based traffic light recognition for autonomous driving

    WANG FAN / CHAI HUAJUN / HUANG KE et al. | European Patent Office | 2019

    Free access