Automatic Recognition and Correction of Volleyball Players’ Release Angle Based on Feature Statistics

Rui Fang,Mu Zhou

doi:10.1155/2021/8103183

Abstract

The constant reform of the competition rules has promoted the innovation of volleyball techniques and tactics. In order to improve the training efficiency and competitive level of volleyball players, this study designed a volleyball player shooting angle automatic recognition and correction method based on the process of feature statistics. Firstly, the basic structure of the information acquisition system is analyzed, and the acquisition process is determined. Then, grayscale and binarization operations are carried out for color-moving images to separate their foreground and background, and a median filtering algorithm is used to remove the image noise. Then, the image pyramid of different sizes is generated by the filter. Based on setting the datum direction, the feature of volleyball shooting is extracted by using the line formula. On this basis, we construct a support vector machine (SVM) classifier to statistically classify the features, use the histogram additive kernel support vector machine method to obtain the lens angle recognition results, and correct the lens angle through feature point matching. Simulation experiments show that this method can effectively remove image noise and make the image signal-to-noise ratio higher, and it can effectively identify whether volleyball players’ release Angle is correct, to achieve the purpose of timely correction.

Highlights

Volleyball is a sport that makes the Chinese people proud, especially the Chinese women’s national volleyball team, which has achieved impressive results in the past and has become a spirit of the times, inspiring the Chinese people to strive for self-improvement [1]
The development of technology in volleyball training has become the goal of future development
The image features are described to obtain a statistical histogram, and with intersection kernel support vector machine (SVM), a linear combination is made between the probabilities of occurrence of different angles, and the highest probability value after the combination is taken as the recognition result [20], and the algorithmic procedure is shown in

Summary

Introduction

Volleyball is a sport that makes the Chinese people proud, especially the Chinese women’s national volleyball team, which has achieved impressive results in the past and has become a spirit of the times, inspiring the Chinese people to strive for self-improvement [1]. Most of the traditional training methods rely on the coaches’ observation and analysis of the angles of the players’ shots through their own experience to find out the deficiencies and give training suggestions and instructions The training in this way relies more on the coaches’ own quality and is somewhat subjective. The reason for the use of feature statistics is that, in the use of mathematical statistics to study overall features, the focus is not on individuals in a population, but on the distribution of related features among different individuals in a population. This paper adopts this method to realize angle recognition, which reduces the complexity of recognition process and improves the accuracy of recognition

Information Acquisition and Processing of Shot Angle

Simulation Experimental Data Analysis and Research

Conclusion