Pedestrian pose estimation can provide a basis for planning and control systems of campus unmanned delivery vehicles to ensure pedestrian safety and improve delivery efficiency. A lightweight pedestrian pose estimation model is built in this paper, and a model training method incorporating campus pedestrian information is proposed. In order to verify the effectiveness of the proposed method and the real-time performance of the model, a comparative experiment is conducted and the real-time performance is tested on the server side and the AGV platform. The results show that the proposed model and training method can efficiently and accurately accomplish campus pedestrian pose estimation in real scene.


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    Title :

    Pedestrian Pose Estimation for Campus Unmanned Delivery Vehicles


    Contributors:
    Jiang, Yuzhu (author) / Li, Ying (author) / Yang, Chao (author) / Wang, Weida (author) / Xu, Bin (author)


    Publication date :

    2023-10-27


    Size :

    2285841 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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