The Construction of Adaptive Learning for Sports Based on Aerobics Trajectory Recognition Model

Abstract

Perceiving the movement track of aerobics is a key element of learning aerobics, but the current aerobics movement is not very professional, the ability to identify the movement track is weak, and improper movement in the movement process is easy to cause physical injury. In order to improve the safety of athletes in bodybuilding training, this paper uses Kinect to hold the coach’s body contour, determine the standard level of coaches’ sports, and combine the characteristics for aerobics training, so as to improve the sports level of coaches, through data acquisition, data processing, and feature extraction to assist sports learning, as well as human posture recognition. The calculation and recognition of human skeleton joints are completed by two algorithms, which improve the human motion recognition algorithm. The aerobics data collected by Kinect device is specified and digitized, which enhances the robustness of the system and improves the performance of the algorithm and the accuracy of the motion data.