Simulation of body trajectory detection in sports training based on infrared thermal imaging image features

Abstract

The traditional motion trajectory detection methods are limited by illumination conditions and occlusion, and it is difficult to capture the athlete’s motion path accurately and in real time. The aim of this study is to improve the accuracy and real-time performance of motion trajectory detection, and to provide more effective auxiliary means for athletes’ training and competition. The image feature analysis method based on Infrared Thermal Imaging, combined with computer vision and machine learning technology, is used to monitor and analyze the motion scene. Infrared Thermal Imaging equipment is used to collect data of motion scenes and obtain infrared image sequence. Then, through the steps of image preprocessing, feature extraction and target recognition, the position and motion trajectory of athletes at different time points are obtained. The experimental results show that the image feature analysis method based on Infrared Thermal Imaging can effectively capture the athlete’s motion trajectory, and has higher accuracy and real-time performance. The method has better adaptability and robustness in complex environments such as lighting conditions and occlusion.