Application of Random Simulation Algorithm in Physical Education and Training

The traditional teaching mode of college physical education is basically based on “teaching”, which can cultivate the knowledge training. However, when faced with tremendous pressures and challenges, college students often exhibit a lack of confidence, courage, and the initiative and consciousness to cooperate with others. In better and progress of society and the cultivation and demand of high-quality talents, there is an urgent need for a newer and more advanced form of physical education. The sports auxiliary training system consists of three parts: sports learning, motion collection, and motion evaluation. The learning module provides fractional content introduction and standard video guidance for sports; The action collection module collects sports standard data and establishes a standard sports action database as a comparison template for sports training; The motion evaluation module is divided into motion recognition and posture recognition. Motion recognition uses DTW algorithm to match corresponding frames for recognition, and posture recognition uses features such as angles and coordinates for posture matching. Both methods can provide scientific auxiliary training and motion guidance to the tester based on the feedback results. Based on the simulation and training, this article has important significance in improving the comprehensive quality of college students and of traditional and training models.