Cited By
View all- Zanganeh AJampour MLayeghi K(2022)IAUFD: A 100k images dataset for automatic football image/video analysisIET Image Processing10.1049/ipr2.1254316:12(3133-3142)Online publication date: 30-May-2022
AI-SAS: Automated In-match Soccer Analysis System
Authors: 
Ning Zhang, Tong Shen, Yue Chen, Wei Zhang, Dan Zeng, Jingen Liu, Tao MeiAuthors Info & Claims
Pages 4515 - 4517
Abstract
Real-time in-match soccer statistics provide continuous tracking of soccer ball and player positions and speeds, enabling advanced analytics. Currently, only elite soccer leagues have the luxury of tracking in-match soccer statistics operated with a large number of trained personnel. In this work, we present an Automated In-match Soccer Analysis System (AI-SAS), using a domain-knowledge-based multi-view global tracking. This system tracks player team, position, and speed automatically, providing real-time in-match team- and individual-level statistics and analyses. In comparison with the latest soccer analysis systems, AI-SAS is more scalable in streaming multiple video sources for real-time process and more flexible in hosting plug-and-play deep-learning-based tracking-by-detection algorithms. The global multi-view tracking also overcomes the single-view limitation and improves the tracking accuracy.
Supplementary Material
Automated In-match Soccer Analysis System (AI-SAS) is a real-time in-match soccer statistics provide continuous tracking\r\nof soccer ball and player positions and speeds, enabling advanced analytics. The system uses a domain-knowledge-based multi-view global tracking. This system tracks player team, position, and speed automatically, providing real-time in-match team- and\r\nindividual-level statistics and analyses. AI-SAS is scalable in streaming multiple video sources for real-time process and more flexible in\r\nhosting plug-and-play deep-learning-based tracking-by-detection algorithms.
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Index Terms
- AI-SAS: Automated In-match Soccer Analysis System
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Information
Published In
October 2020
4889 pages
ISBN:9781450379885
DOI:10.1145/3394171
- General Chairs:
- Chang Wen Chen,
- Rita Cucchiara,
- Xian-Sheng Hua,
- Program Chairs:
- Guo-Jun Qi,
- Elisa Ricci,
- Zhengyou Zhang,
- Roger Zimmermann
Copyright © 2020 Owner/Author.
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Published: 12 October 2020
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View all- Zanganeh AJampour MLayeghi K(2022)IAUFD: A 100k images dataset for automatic football image/video analysisIET Image Processing10.1049/ipr2.1254316:12(3133-3142)Online publication date: 30-May-2022
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