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

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.

Labeling Out-of-View Objects in Immersive Analytics to Support Situated Visual Searching

“…To understand current practice and identify gaps in badminton coaching, we interviewed five professional badminton players and coaches (I1-I5; M = 2, F = 3; Age: [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45]. All of them are former Olympic players representing Canada, Taiwan, and the US.…”

“…Prior studies have addressed shuttlecock detection and tracking, including an instant review system to determine whether a shot was in or out [22]. Other studies focused on tracking the speed, rotation angle, and athlete's body transformation using sensors and path-tracking algorithms [34]. Recently, MonoTrack [31] improved state-of-the-art models [14,19,54] on court recognition and 2D trajectory estimation based on badminton domain knowledge.…”

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

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”