Research on the Application of Intelligent Analysis Model for Educational Content in Higher Education Physical Training

Abstract

Intelligent technology brings brand new possibilities for education and teaching by virtue of its powerful computing and learning capabilities. Aiming at the problems of low efficiency and poor error correction effect of the current means of correcting sports training errors, this paper uses intelligent analysis technology to design a sports training error detection model to automatically measure the training process so as to realize the measurement and analysis of training errors. The model divides the video image as candidate foreground and candidate background by combining the Bayesian decision-making method and inter-frame difference method and sets the initial value of this background as the main component analysis method to obtain the real-time detection results of target posture. The analysis of the model’s sports posture detection shows that the recognition rate of this paper’s algorithm for different sports is more than 81%, and the error rate and accuracy are 0.038% and 95.9%, which has a better sports training error detection accuracy. After applying the intelligent analysis model to actual sports training, the 100-meter run and standing long jump scores of the students trained with the intelligent analysis model are 3.52 points and 0.9 points higher, which proves that the sports training error detection model promotes sports training.

Keywords

• bayesian decision making
• inter-frame differencing
• principal component analysis
• error detection
• intelligent analysis
• sports training
• 97m80