Analysis of Athletes’ Training Characteristics Based on Action Statistics of Image Processing

Abstract

Sports and physical exercise are so closely related that they cannot be described separately. The standardization of physical movements requires athletes to constantly improve their planning. Only when they approach the standard, the improvement of sports level is just around the corner. However, the traditional training standard method is limited by human factors and backward technology, and there are many drawbacks, and athletes’ training cannot reach the best state. In this paper, image deblurring is processed to get the reconstruction model of high-resolution image. Through the experiment on the statistics of the competition, the movement of transfer, out of bounds and arm holding in the standing stage, and the movement of rolling bridge and lifting and holding in the kneeling stage are predicted and prevented. For 55 kg, the key to win is the rolling bridge and lifting action; 60 kg attaches importance to the importance of tactical defense. These two lightweight competitions focus on comprehensive training, while the 120 kg heavyweight competition is more in pursuit of strength. Finally, the experiment runs well, and the data and effect can meet the design goal of this paper. The specific details of the optimization and improvement need to be improved in the next step.