Research on the Positioning Technology of Sports 3D Teaching Action Based on Machine Vision

HARI MOHAN PANDEY*, LIU-Hao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a method of action location in three-dimensional motion teaching. The machine vision technology is used to solve the problems of low positioning accuracy and long positioning time in the traditional motion three-dimensional teaching method. The work of this method is as follows: (a) using machine vision method to determine the world coordinate system of the image; (b) using MRF algorithm to extract the features of 3D teaching action image; (c) determining the spatial correlation of 3D teaching action data. In the three-dimensional teaching action image, the smooth filtering technology is used to suppress and eliminate the noise. Then the convolution neural network (CNN) is used to reconstruct the three-dimensional teaching action image. The entropy of three-dimensional teaching behavior of physical education is determined by CNN. Through a large number of computer simulations, the effectiveness of the proposed system is confirmed. The results show that the system achieves 95% accuracy when the positioning time is 1.9s.
Original languageEnglish
Article numberMONE-D-21-00135_R1
JournalMobile Networks and Applications
Publication statusAccepted/In press - 23 May 2021

Keywords

  • Machine vision
  • 3D teaching action
  • Positioning technology
  • Smoothing filtering technology.

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