Video Sequence Analysis for On-Table Tennis Player Ranking and Analysis

Xiaoni Wei

doi:10.4018/ijmcmc.293750

Abstract

With the rapidly developing of the scientific research in the field of sports, big data analytics and information science are used to carry out technical and tactical statistical analysis of competition or training videos. The table tennis is a skill oriented sport. The technique and tactics in table tennis are the core factors to win the game. With the endlessly emerging innovative playing techniques and tactics, the players have their own competition styles. According to the competition events among athletes, the athletes’ competition relationship network is constructed and the players’ ranking is established. The ranking can be used to help table tennis players improve daily training and understand their ability. In this paper, the table tennis players’ ranking is established their competition videos and their prestige scores in the table tennis players’ competition relationship network.

Highlights

With the rapid development of information technology, artificial intelligence (AI) (Dwivedi et al 2019; Vaishya et al 2020), Internet of Things (IoT) and cloud computing (Jahantigh et al 2019; Haji et al 2020) have been widely used in social development
The intelligent technical and tactical statistical analysis of video data combined with machine learning has been widely applied in athletic sports training and competition (Herold et al 2019; Wenninger et al 2020)
This paper considers tactical indicators, technical indicators, landing point indicators and gain and loss indicators by combining with the special characteristics of table tennis and taking the video technical and tactical statistical indicators of table tennis competition as the starting point

Summary

INTRODUCTION

With the rapid development of information technology, artificial intelligence (AI) (Dwivedi et al 2019; Vaishya et al 2020), Internet of Things (IoT) and cloud computing (Jahantigh et al 2019; Haji et al 2020) have been widely used in social development. The intelligent technical and tactical statistical analysis of video data combined with machine learning has been widely applied in athletic sports training and competition (Herold et al 2019; Wenninger et al 2020). With the help of the analysis of index system, it can effectively reflect the essential characteristics and laws of technical and tactical in the competition to construct statistical index system for table tennis techniques and tactics. The index system is constructed according to technical and tactical video statistics for table tennis competition. The complex network is adopted to analyze the table tennis training or competition data.

EXPERIMENTS AND SIMULATIONS

CONCLUSION