Badminton Path Tracking Algorithm Based on Computer Vision and Ball Speed Analysis

Haibin Lv,Yi Lyu,Shumin Zhang

doi:10.1155/2021/3803387

Haibin Lv, Yi Lyu + Show 1 more

Open Access

https://doi.org/10.1155/2021/3803387

Copy DOI

Abstract

With the development of artificial intelligence and the rapid development of the computer industry, the practicability of computer vision programs is gradually improved. In this paper, the badminton path tracking algorithm based on computer vision analyzes the badminton trajectory and speed. This paper is aimed at analyzing the image processing technology and path tracking algorithm by using computer vision to obtain relevant data and then exploring the factors of badminton path and ball speed transformation, which provides reference significance for badminton players in future training. The path tracking algorithm is used to predict the rotation angle, the ball speed, and the athlete’s body information during the badminton movement through sensors, and the position information of the moving target is captured based on the visual field tracking and target dynamic tracking. Combined with specific badminton players, we first analyze the angle of each limb and the speed of the racket in the process of movement and record the data. Determine different positioning points for different actions, such as pushing the ball, picking the ball, hooking the ball, and rubbing the hair. In this process, we aim at the connection between the highest point and the lowest point of the badminton trajectory and the ball speed. This process fully combines the theoretical knowledge of the path tracking algorithm. The experimental results show that different service skills have different effects on the trajectory and speed of badminton. In the test of relevant data by using the push and receive skills, the lowest point of the ball served by player A in the first three times is higher than that by player B. The most significant difference between the lowest points of the five times is the second time, with a difference of 0.2 m, and the third time, with a minimum difference of 0.03 m.

Highlights

With the development of science and technology, especially the advancement of computing power and the popularization of computer-related applications, people’s demand for the use of computer technology to perceive and understand the world is increasing [1]
The research of computer vision is largely focused on the content of the image
Vision-based field tracking and target dynamic tracking mainly use computer vision technology to discover, analyze, and process the field to be tracked in the incoming video clips, capture the position information of the moving target, and predict and track the impact position of the field

Summary

Introduction

With the development of science and technology, especially the advancement of computing power and the popularization of computer-related applications, people’s demand for the use of computer technology to perceive and understand the world is increasing [1]. The research object of computer vision is mainly a three-dimensional scene mapped onto single or multiple images, such as the reconstruction of a three-dimensional scene. Pattern recognition uses various methods to extract information from signals, mainly using statistical theories. One of the main directions in this field is to extract information from image data. Path tracking in the field of computer vision is a cross-discipline that integrates graphics and image processing, intelligent systems, and procedural control. It has unique advantages in the application of industrial production control, and its applications can be found in every aspect of life.

Objectives

Methods

Discussion

Conclusion