Analysis of the current situation and teaching strategies of university table tennis teaching in the context of big data

被引:0
|
作者
Wang J. [1 ]
Li Y. [1 ]
机构
[1] Sports Department, Shaanxi Fashion Engineering University, Shaanxi, Xi'an
关键词
Aberrations; Binocular stereo vision; Least squares; Table tennis teaching; Three-dimensional reconstruction;
D O I
10.2478/amns.2023.2.00187
中图分类号
学科分类号
摘要
As an important part of university physical education, table tennis teaching occupies a crucial position in physical education reform and requires continuous innovation and reform. This paper first starts from the current situation of table tennis teaching and proposes the application of a binocular stereo vision system based on a binocular stereo vision system for university table tennis teaching, which lays the foundation for three-dimensional reconstruction and skill learning. Secondly, the mathematical model of the 3D reconstruction algorithm is constructed by the tangential distortion of least squares, which avoids the complex algorithm of iteratively solving the 3D world coordinates of table tennis and improves the speed of the 3D reconstruction algorithm while the accuracy meets the subsequent prediction requirements. Finally, students in the experimental and control groups were compared in the technical evaluation of table tennis backhand pushing, attacking techniques, and left pushing and right attacking to verify the effectiveness of the table tennis binocular stereo vision teaching system. The study results showed that the experimental group students trained by the binocular stereo vision system for table tennis had 41.77% higher accuracy, 23.13% higher coordination, 12.31% higher return speed, and 14.84% higher hitting power compared to the control group. Applying a binocular stereo-vision system to table tennis teaching is novel and is conducive to stimulating students' curiosity and challenge, enhancing their interest in learning, and effectively improving their understanding and knowledge of table tennis techniques. © 2023 Jingli Wang et al., published by Sciendo.
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