Application of Dynamic Image Simulation Based on Optical Sensor Networks in Optimizing the Quality of Physical Education Course Videos

Abstract

Abstract With the development of video physical education course management simulation, in order to improve the quality of video transmission, this study proposes a video transmission technology based on optical flow estimation network. Firstly, an optical flow estimation network model is established, which can automatically extract optical flow information from input video and estimate object motion by analyzing pixel displacement between successive images. Then, according to the optical flow information, the video frame is repaired and compensated to reduce the information loss and quality degradation in video transmission. The experimental results show that the video transmission technology based on optical flow estimation network can significantly improve the quality and stability of video. Compared with the traditional video transmission method, this technology has better adaptability and robustness in the case of low network bandwidth or network congestion, and provides high quality and stable video transmission, which provides strong support for the application of distance education and sports course management simulation.