Research on the evaluation of sports training effect based on artificial intelligence technology

Abstract

In artificial intelligence, virtual environment and reality technology are one of the most popular types of research. The integration of graphics, images and human action recognition technology is the focus of improving training methods in sports training. Therefore, the research combines dynamic time warping algorithm and Local image feature action recognition combined with virtual technology is applied to sports training to improve training effects and competition results. The results show that the overall accuracy of the research model is 20% higher than that of the traditional gesture recognition system, and the action recognition accuracy of the self-collected data set reaches more than 90%. In the empirical analysis, the posture recognition system has a good anti-interference ability with a recognition accuracy of about 95% for different parts of the body. Athletes' overall satisfaction with the system reaches more than 90 points, effectively improving the training effect and competition performance.