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

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Proceedings of Congress on Control, Robotics, and Mechatronics (CRM 2023)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 364))

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Abstract

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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Authors and Affiliations

  1. Department of Computer Science and Engineering, Poornima University, Jaipur, Rajasthan, India

    Babita D. Sonare & Deepika Saxena

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  1. Babita D. Sonare
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  2. Deepika Saxena
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Correspondence to Babita D. Sonare .

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Editors and Affiliations

  1. Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee, India

    Pradeep Kumar Jha

  2. Department of Mechanical Engineering, Rajasthan Technical University, Kota, Rajasthan, India

    Brijesh Tripathi

  3. Department of Mechanical and Mechatronic Engineering, UCSI University, Cheras, Kuala Lumpur, Malaysia

    Elango Natarajan

  4. Department of Computer Engineering, Rajasthan Technical University, Kota, Rajasthan, India

    Harish Sharma

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Sonare, B.D., Saxena, D. (2024). A Vision-Based Feature Extraction Techniques for Recognizing Human Gait: A Review. In: Jha, P.K., Tripathi, B., Natarajan, E., Sharma, H. (eds) Proceedings of Congress on Control, Robotics, and Mechatronics. CRM 2023. Smart Innovation, Systems and Technologies, vol 364. Springer, Singapore. https://doi.org/10.1007/978-981-99-5180-2_41

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  • DOI: https://doi.org/10.1007/978-981-99-5180-2_41

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-5520-6

  • Online ISBN: 978-981-99-5180-2

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