IET Image Processing (Jan 2023)

Research on the application of body posture action feature extraction and recognition comparison

  • Jia‐Jun Zhao,
  • Zhi‐Qiang Liu,
  • Si‐Jia Xie,
  • Chuan‐Qian Tang

DOI
https://doi.org/10.1049/ipr2.12620
Journal volume & issue
Vol. 17, no. 1
pp. 104 – 117

Abstract

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Abstract This paper mainly conducts a comparative study of body posture action feature extraction and recognition in three‐dimensional (3D) space through motion capture technology and virtual reality technology. Firstly, this paper proposes a body posture feature extraction method in 3D space to obtain joint point data and conduct body posture feature extraction research. At the same time, this method is used for action recognition research, which solves the difficulty of traditional methods in 3D scene feature extraction and motion recognition. In addition, this paper proposes two action comparison methods in 3D space. One is a ‘distance threshold method’ that calculates the distance between bones in the form of joint points and bones, which can finally provide the effect of dynamic display of sliders; the other is the ‘feature plane method’ that calculates the detailed information based on different skeletal joint point planes, and finally provides a text display effect with detailed body posture difference values. Finally, combined with virtual reality technology, an application platform for body posture feature recognition and comparison is designed and implemented, which solves the problems of poor visualization effect and weak interaction of traditional methods.