Investigation on Motion Teaching Video Compression Algorithm Based on Artificial Intelligence

Abstract

Sports are a common activity of human beings, and their development levels vary in different fields. With the continuous progress of science and technology and the increasing level of computer technology, many new algorithms have emerged. This article mainly studied the method and implementation principle of Motion Teaching Video Compression (MTVC) based on artificial intelligence, and verified through MATLAB language simulation experiments the problems and improvement measures in the storage, processing, and output result analysis of commonly used data under the applicable parameters of this control strategy. Finally, the functionality of the algorithm model was tested. The test results showed that the compression ratio of the system was above 85%. The video clarity was very high, and the video bitrate was above 720kbps. The video decoding time was within 3 to 5 seconds. This could improve the compression effect of traditional sports teaching videos and enhance students' interest in learning.