Motion training recognition based on thermal radiation imaging system and object detection: Human motion thermal image monitoring

Abstract

A human motion monitoring method based on thermal radiation image system and target detection technology is developed. The heat distribution of human body in motion is captured by thermal image, and the real-time recognition and analysis of human motion is realized by combining image processing and target detection algorithm. A complete set of thermal radiation optical image monitoring system is designed in this study. A high-sensitivity thermal imaging camera is used to capture the thermal radiation images of the human body in the process of motion, and these images are then transmitted to the data acquisition unit for preliminary data collation and storage. The image processing module preprocesses the acquired thermal images, and the preprocessed images are fed into the object detection algorithm, which is based on the deep learning framework and can recognize and classify different movements of the human body. The thermal radiation image monitoring system can accurately capture the thermal image of the human body in different motion states, and identify the movement type of the athlete in real time through the target detection algorithm. The system has a strong ability to capture the details of actions, and can identify the beginning, progress and end stages of actions. Compared with traditional monitoring methods, the thermal radiation light image monitoring system has obvious advantages in terms of data accuracy and real-time performance. This method can not only provide high precision movement recognition, but also has the advantages of non-contact and real-time monitoring, which greatly improves the efficiency and accuracy of sports training monitoring.