Modeling and Intelligent Analysis of the Theoretical Framework of Multi-Angle Image-Assisted Physical Training based on Data-Oriented Physical Exercise Experience

Modeling and intelligent analysis of the theoretical framework of the multi-angle image-assisted physical education teaching based on data-oriented physical exercise experience is studied in the paper. The proposed study has improved the traditional region growing algorithm with the help of a multi-view distance image by utilizing the center of gravity in the point cloud region corresponding to the distance image as the seed point ensures the stability of seed point selection. With this integration, the systematic model is then implemented through the theoretical framework of multi-angle image-assisted physical training. According to the existing study, deep learning simulates the core hierarchical abstract structure of the biological visual system and makes full use of the rich information hidden, and this has been used to improve the general quality of the system. The performance is then validated by testing process.