Evaluation of sports training quality based on infrared thermal images and data mining: Analysis of body thermal energy consumption

The research proposes a method for evaluating the quality of sports training based on infrared thermal images and data mining. It uses infrared thermal image technology to objectively and accurately assess the quality of sports training, and combines data mining technology to predict the effect of sports training, providing scientific guidance for sports training. The research designed a sports training quality evaluation and prediction system, including the test of the sports action acquisition model and the sports quality assessment system. The body thermal image data during the movement process is collected by using infrared thermal imagers, and the characteristics of body thermal energy consumption are extracted through image processing and analysis. Then, data mining technology is applied to preprocess the motion data, construct a data mining model, and establish a motion training prediction and optimization model to analyze the relationship between different motion actions and the body's energy consumption, thereby evaluating the quality of motion training. The experimental results show that this method can effectively evaluate the quality of sports training and provide scientific guidance for sports training. The research conclusion is that the sports training quality evaluation method based on infrared thermal images and data mining has the advantages of objectivity, accuracy and efficiency, and can provide strong technical support for sports training.