Quality Evaluation and Informatization Analysis of Physical Education Teaching Reform Based on Artificial Intelligence

Abstract

With the continuous reform of China’s education and the development of the educational environment, English will no longer be the third subject for Chinese students and physical education will replace it as the third subject. The teaching mode has also gradually changed from the traditional artificial mode to the current smart education. In the context of artificial intelligence, physical education can also apply this technology to daily teaching. After physical education becomes the third subject, it is necessary to reform the existing teaching mode and conduct quality evaluation and informatization analysis. In order to achieve this effect, we use artificial intelligence action scenes to detect students' detailed actions and identify key actions and then use computer vision system to create regression models and Bayesian formulas to give the criteria for judging the subsequent training points of the computer. Then, according to the training data of each student in the training process, the quality analysis and informatization evaluation of the teaching reform of physical education are carried out. Using the action bank algorithm as the basic algorithm of feature extraction, a template research method based on multispectral clustering is proposed to facilitate its dissemination in the computer background database. Then, through experiments to compare the before and after optimization of the algorithm, the data analysis of the resolution, time consumption, and detection error of the action bank model were carried out, and it was found that the performance was improved. Then, by means of mean shift detection method and spatiotemporal action detection method, the resolution, time consumption, and detection error of the action bank model are optimized to achieve the quality evaluation and informatization analysis of physical education teaching reform.