Binocular Vision-Based Recognition Method for Table Tennis Motion Trajectory

Abstract

The latest development in computer technology in sports has increased the popularity of ping pong among people. It calls for designing an intelligent table tennis robot using computer technology to cooperate with table tennis enthusiasts and professional table tennis players to practice. Much research work has already been done in this area. However, this study explores the use of binocular vision to precisely identify, locate, and anticipate the flight trajectory and landing position of table tennis balls. Major issues addressed in this study include identifying fast-moving ping pong balls, calibrating the camera, obtaining the camera’s internal and external settings, and localizing the ping pong balls in three dimensions. A new target recognition method is proposed in combination with the actual needs of the combat ping pong robot. The method combines colour segmentation, background subtraction, and ellipse fitting, which can detect the tail range of flying ping pong balls and find the centre position of the balls. Based on the ellipse fitting analysis of the image, characteristics of the tail of the flying ping pong ball are studied. This study can aid in tracking the trajectories of high-speed flying objects, which is helpful for both aerospace and military industries.