3D motion trajectory prediction based on optical image remote sensing data in sports training simulation

Remote sensing technology has the disadvantages of limited multi-spectral remote sensing data and wide interval. Optical image remote sensing technology makes up for the shortcomings of the previous remote sensing technology and opens up a new way for the study of computer vision. How to explore the development of intelligent sports test and analyze the innovation and expansion of Internet in college sports test training has become a hot research direction of college sports test interconnection. The trajectory prediction problem in current sports training and the application potential of optical image remote sensing data in sports field are studied and analyzed. The aim is to achieve accurate and real-time 3D trajectory prediction by using optical image remote sensing data. The study describes in detail the predictive model construction process, including the application of optical image processing, feature extraction, and machine learning algorithms, analyzes the effectiveness of the trained model in predicting the 3D trajectory of specific sports items in sports training, and compares it with existing methods. The results show that the 3D motion trajectory prediction method based on optical image remote sensing data is accurate and real-time, and can be effectively applied in sports training. This research provides a new idea and method for the motion trajectory prediction of sports training, which is helpful to improve the effect and results of sports training.