CASIA OpenIR  > 多模态人工智能系统全国重点实验室  > 三维可视计算
Soccer Match Broadcast Video Analysis Method Based on Detection and Tracking
Li HY(李红雨)1; Yang M(杨猛)1,2; Yang C(杨超)1; Kang JL(康江浪)1; Xiang Suo3; Meng WL(孟维亮)4,5; Zhen Li3; Lijuan Mao3; Bin Sheng6; Jun Qi7
Source PublicationComputer Animation and Virtual Worlds
2024
Volume35Issue:3Pages:1-17
Abstract

We propose a comprehensive soccer match video analysis pipeline tailored for broadcast footage, which encompasses three pivotal stages: soccer field localization, player tracking, and soccer ball detection. Firstly, we introduce sports camera calibration to seamlessly map soccer field images from match videos onto a standardized two-dimensional soccer field template. This addresses the challenge of consistent analysis across video frames amid continuous camera angle changes. Secondly, given challenges such as occlusions, high-speed movements, and dynamic camera perspectives, obtaining accurate position data for players and the soccer ball is non-trivial. To mitigate this, we curate a large-scale, high-precision soccer ball detection dataset and devise a robust detectionmodel, which achieved the mAP50−95 of 80.9%. Additionally, we develop a high-speed, efficient, and lightweight tracking model to ensure precise player tracking. Through the integration of these modules, our pipeline focuses on real-time analysis of the current camera lens content during matches, facilitating rapid and accurate computation and analysis while offering intuitive visualizations.

Language英语
WOS IDWOS:001233750100001
Sub direction classification图像视频处理与分析
planning direction of the national heavy laboratory环境多维感知
Paper associated data
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/57164
Collection多模态人工智能系统全国重点实验室_三维可视计算
Corresponding AuthorLi HY(李红雨); Yang C(杨超); Lijuan Mao
Affiliation1.School of Information science and Technology, Beijing Forestry University, Beijing, China
2.Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing, China
3.School ofAthletic Performance, Shanghai University of Sport, Shanghai, China
4.State Key Laboratory ofMultimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
5.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
6.Department of Computer Science and Engineering, Shanghai Jiao Tong Univerity, Shanghai, China
7.Department of Computing, Xi’an JiaoTong-Liverpool University, Suzhou, China
Recommended Citation
GB/T 7714
Li HY,Yang M,Yang C,et al. Soccer Match Broadcast Video Analysis Method Based on Detection and Tracking[J]. Computer Animation and Virtual Worlds,2024,35(3):1-17.
APA Li HY.,Yang M.,Yang C.,Kang JL.,Xiang Suo.,...&Jun Qi.(2024).Soccer Match Broadcast Video Analysis Method Based on Detection and Tracking.Computer Animation and Virtual Worlds,35(3),1-17.
MLA Li HY,et al."Soccer Match Broadcast Video Analysis Method Based on Detection and Tracking".Computer Animation and Virtual Worlds 35.3(2024):1-17.
Files in This Item: Download All
File Name/Size DocType Version Access License
Computer Animation (5439KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Li HY(李红雨)]'s Articles
[Yang M(杨猛)]'s Articles
[Yang C(杨超)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Li HY(李红雨)]'s Articles
[Yang M(杨猛)]'s Articles
[Yang C(杨超)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Li HY(李红雨)]'s Articles
[Yang M(杨猛)]'s Articles
[Yang C(杨超)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Computer Animation Virtual - 2024 - Li - Soc.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.