Affiliation:
1. College of Arts and Sciences, Yangtze University, Jingzhou 434020, China
Abstract
Soccer (football) is a popular form of exercise on the planet. There are a lot of individuals who tune into football matches in real time on television or the Internet. A game of American football lasts 90 minutes, but to save time, spectators may simply want to see a few highlights. As far as we know, no such tool exists that can be used to extract intelligent highlights from a football match. In this research, we present a technique for clever editing of live football matches. Our technology allows for the automatic extraction of key players’ goals, shots, corner kicks, red and yellow cards, and the presence of key players from a football match’s live stream. During the 2018 FIFA World Cup, our solution was integrated into live streaming platforms and it functioned admirably.
Subject
Computer Networks and Communications,Computer Science Applications
Reference34 articles.
1. From the Laboratory to the Field: IMU-Based Shot and Pass Detection in Football Training and Game Scenarios Using Deep Learning
2. What happened next? Using deep learning to value defensive actions in football event-data;C. Merhej
3. Football match intelligent editing system based on deep learning;B. Wang;KSII Transactions on Internet and Information Systems (TIIS),2019
4. Deep learning based Football player’s Health Analysis;M. R. Begum;Journal For Innovative Development in Pharmaceutical and Technical Science (JIDPTS),2021
5. Hybridized Hierarchical Deep Convolutional Neural Network for Sports Rehabilitation Exercises
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献