Real-time body movement tracking of athletes via a CNN-based approach

Sports injuries frequently stem from improper poses and movements. This paper explores the potential of using video and deep neural network model in mitigating such risks. A novel real-time body movement tracking system is designed to enable athletes to analyze and refine their techniques without the need for intrusive sensors. Central to our approach is the development of a user-friendly graphical interface, facilitating the effortless display and examination of tracked movements. This system not only enhances athletic performance but also aims to significantly reduce the sports injuries.