Application of Big Data Analysis and Image Processing Technology in Athletes Training Based on Intelligent Machine Vision Technology

Abstract

With the rapid development of machine vision technology in recent years and the rapid increase of various video data, image processing and behavior recognition based on video data have become one of the hot research topics nowadays. This paper mainly studies the application of big data analysis and image processing technology in athlete training, the time-segmenting two-stream network based on sparse sampling adopted in this paper can better express the long-term motion characteristics. Firstly, the continuous video frame data is divided into several segments, and each segment of video frame sequence is randomly sampled to form a short sequence data containing user actions, and then the feature extraction is carried out by using double-stream network. In this paper, the proposed algorithm model is simulated and compared with other algorithms. The experimental results show that the recognition rate of the proposed model is the best among several algorithms.