Table Tennis Service Umpiring System Based on Video Identification—for Height and Angle of the Throwing Ball

Abstract

Table tennis is a very rapid movement in competitive sports, and its referee needs to make a judgment based on observation and experience within a few seconds, which is a very challenge task. Due to the subjective judgment of the referee’s uncertainty and imprecision, it will lead to some false judgment, resulting in a significant impact on the results of the competition. In the current competitions, the most controversial penalty is the height and angle of the throwing ball’s problem. To solve this controversial problem, this paper designs a complementary video-based recognition of table tennis service umpiring system that can identify and track the location of the table tennis in the video and determine the exact moment when the ball leaves the hand. As a new umpiring system, this paper first introduces into the machine learning methods to identify in table tennis, and discusses a new method of predicting the region of interest to reduce the recognition error rate and improve the recognition efficiency. This system will eventually get through the data of height and angle of the throwing ball, which not only provides a scientific reference for the referees, but also provides a supplementary basis for the athletes to question the referee.