Application of Depth Learning Algorithm in Automatic Processing and Analysis of Sports Images

With the rapid development of sports, the number of sports images has increased dramatically. Intelligent and automatic processing and analysis of moving images are significant, which can not only facilitate users to quickly search and access moving images but also facilitate staff to store and manage moving image data and contribute to the intellectual development of the sports industry. In this paper, a method of table tennis identification and positioning based on a convolutional neural network is proposed, which solves the problem that the identification and positioning method based on color features and contour features is not adaptable in various environments. At the same time, the learning methods and techniques of table tennis detection, positioning, and trajectory prediction are studied. A deep learning framework for recognition learning of rotating flying table tennis is put forward. The mechanism and methods of positioning, trajectory prediction, and intelligent automatic processing of moving images are studied, and the self-built data sets are trained and verified.