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

Authors: Hao, L. and Pandey, H.M.

Journal: Mobile Networks and Applications

Volume: 27

Issue: 6

Pages: 2419-2428

eISSN: 1572-8153

ISSN: 1383-469X

DOI: 10.1007/s11036-021-01885-4

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 1.9 s.

Source: Scopus

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

Authors: Hao, L. and Pandey, H.M.

Journal: MOBILE NETWORKS & APPLICATIONS

Volume: 27

Issue: 6

Pages: 2419-2428

eISSN: 1572-8153

ISSN: 1383-469X

DOI: 10.1007/s11036-021-01885-4

Source: Web of Science (Lite)