This project aims to explore action recognition through a deep learning model generated by Convolutional Neural Networks, establishing the foundation for human-robot interaction in a scenario where Unmanned Aerial Vehicles (UAV) are controlled exclusively by visual commands. The model analyzes images captured by an onboard camera using and classifies them into nine categories. Each category issues a specific command based on human actions performed by individuals properly equipped with personal protective equipment. The results demonstrate the feasibility of the proposed approach, opening room for improvements aiming its use in more complex scenarios.


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    Title :

    Recognizing Human Actions: A Deep Learning Model for UAV Piloting




    Publication date :

    2024-11-13


    Size :

    3576278 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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