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Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
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Abstract

Human gesture recognition and motion representation have become a vital base of current intelligent human-machine interfaces because of ubiquitous and more comfortable interaction. Human-gesture recognition chiefly deals with recognizing meaningful, expressive body movements involving physical motions of the face, head, arms, fingers, hands, or body. This review article presents a concise overview of optimal human gesture and motion representation of medical images. It surveys various works undertaken on human gesture design and discusses various design methodologies used for image segmentation and gesture recognition. It further provides a general idea of modeling techniques for analyzing hand gesture images and even discusses the diverse techniques involved in motion recognition. This survey provides insight into various efforts and developments made in the gesture/motion recognition domain by analyzing and reviewing the procedures and approaches employed for identifying diverse human motions and gestures for supporting better and devising improved applications in the near future.

© 2024 The Author(s). Published by Bentham Open.
© 2024 The Author(s). Published by Bentham Open. This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
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2024-01-01
2024-11-23

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Review for Optimal Human-gesture Design Methodology and Motion Representation of Medical Images using Segmentation from Depth Data and Gesture Recognition
Curr. Med. Imaging 20, E300523217435 (2024); https://doi.org/10.2174/1573405620666230530093026
/content/journals/cmir/10.2174/1573405620666230530093026
/content/journals/cmir/10.2174/1573405620666230530093026
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  • Article Type:     Review Article
Keyword(s): Gesture recognition; Hand gesture; Human gesture; Image segmentation; Machine vision; Motion recognition

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