Application of posture estimation optimization algorithm in the analysis of college air volleyball teaching movements

The advent of computer technology and the modernization of sports education have led to an increasing reliance on intelligent technology in the field of sports education. To improve the application effect of intelligent technology in physical education, a volleyball motion analysis technology combined with pose estimation optimization algorithm is designed. During the process, Kinect collects the joint data of the research object, which is then combined with the commonly used background subtraction and frame difference optimization techniques. This results in the construction of a background model. The background update number in the initial frame is utilized as the reference value. The contour edge is smoothed through the application of a one-dimensional Gaussian kernel function, and a teaching action guidance system is designed. The experimental results showed that the average accuracy of the research method reached 79.7 % and the average recall rate reached 75.2 %. The average relative error of the method was 4.13 % when comparing the accuracy of human body model. The research method is validated to accurately capture and analyze volleyball motion, which can provide some technical help for sports teaching.