Gait recognition has become more popular and significant in the recent years due to security concerns since it can be carried out remotely without authorization. This article discusses the vision-based model and model-free feature extraction methods for identifying human gaits. Both methods are distinctive in and of themselves. The structural parts of the human body are dealt with via model-based approaches, including joint locations, joint angles, stride length/cadence, and 2D stick figures. Model-free techniques, including gait energy image, absolute frame difference image, gait history image, etc., give spatiotemporal information on gait silhouettes. Subject identification is made based on the high rate of recognition after approach-wise features are provided to classifiers. The important characteristics will then stand out.


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    Titel :

    A Vision-Based Feature Extraction Techniques for Recognizing Human Gait: A Review


    Weitere Titelangaben:

    Smart Innovation, Systems and Technologies


    Beteiligte:
    Jha, Pradeep Kumar (Herausgeber:in) / Tripathi, Brijesh (Herausgeber:in) / Natarajan, Elango (Herausgeber:in) / Sharma, Harish (Herausgeber:in) / Sonare, Babita D. (Autor:in) / Saxena, Deepika (Autor:in)

    Kongress:

    Congress on Control, Robotics, and Mechatronics ; 2023 ; Kota, India March 25, 2023 - March 26, 2023



    Erscheinungsdatum :

    2023-11-10


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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