An artificial intelligence and machine vision based evaluation of physical education teaching

Issue title: Impact of Intelligence Methodologies on Education and Training Process

Guest editors: Vijayalakshmi Saravanan

Article type: Research Article

Authors: YanRu, Liu^{; *}

Affiliations: Southwest University of Political Science & Law Chongqing, China

Correspondence: [*] Corresponding author. Liu YanRu, Southwest University of Political Science & Law Chongqing 401120. E-mail: lyanru@aol.com.

Abstract: The manual evaluation method to evaluate the effect of physical education teaching is tedious, and it will have a large error when the amount of data is large. In order to improve the efficiency of physical education evaluation, this article uses artificial intelligence for data analysis and uses machine vision to identify the teaching process to assist teachers in physical education. In order to reduce the calibration error of the parameters and obtain more accurate camera imaging geometric parameters, this paper adopts the method of averaging multiple sample points to determine the calibration parameters of the camera. In addition, this study builds system function modules according to actual needs and verifies system performance through experimental teaching methods. The research results show that the model proposed in this paper has a certain practical effect.

Keywords: Artificial intelligence, machine vision, physical education, effect evaluation

DOI: 10.3233/JIFS-189392

Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3559-3569, 2021