Current Medical Imaging

Author(s): Anju Gupta*, Sanjeev Kumar and Sanjeev Kumar

DOI: 10.2174/1573405620666230530093026

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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

Article ID: e300523217435 Pages: 14

  • * (Excluding Mailing and Handling)

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.

Keywords: Human gesture, Hand gesture, Motion recognition, Image segmentation, Gesture recognition