Application of VR motion intelligent capture based on DLPMA algorithm in sports training

Abstract

With the rapid development of Virtual Reality (VR) technology, its application in the field of sports training is also receiving increasing attention. This study applies the Distance Likelihood Based Probabilistic Model Averaging (DLPMA) algorithm to the VR motion intelligent capture system, aiming to provide an efficient and accurate motion data collection method to improve existing sports training methods. Introduced the design and implementation of a VR motion intelligent capture system based on DLPMA algorithm, and applied it to sports training. By conducting comparative experiments with traditional training methods, the advantages of the system in motion capture accuracy, real-time performance, and user experience are verified. The research results indicate that the system can accurately capture the movements of athletes and provide timely feedback to users, providing an effective auxiliary means for sports training. Although the system has shown good performance in sports training, there are still some limitations. Future research can further optimize algorithms, enhance system stability and flexibility, to meet a wider range of sports training needs.