Kapela, Rafal, McGuinness, Kevin ORCID: 0000-0003-1336-6477, Świetlicka, Aleksandra and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 (2015) Real-time event detection in field sport videos. In: Computer Vision in Sports. Advances in Computer Vision and Pattern Recognition . Springer, pp. 293-316. ISBN 978-3-319-09395-6
Abstract
This chapter describes a real-time system for event detection in sports broadcasts. The approach presented is applicable to a wide range of field sports. Using two independent event detection approaches that work simultaneously, the system is capable of accurately detecting scores, near misses, and other exciting parts of a game that do not result in a score. The results obtained across a diverse dataset of different field sports are promising, demonstrating over 90% accuracy for a feature-based event detector and 100% accuracy for a scoreboard-based detector detecting only scores
Metadata
Item Type: | Book Section |
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Refereed: | Yes |
Subjects: | Computer Science > Machine learning Engineering > Signal processing Computer Science > Multimedia systems Computer Science > Image processing Computer Science > Digital video |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering Research Initiatives and Centres > INSIGHT Centre for Data Analytics DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing |
Publisher: | Springer |
Official URL: | http://www.springer.com/computer/image+processing/... |
Copyright Information: | © 2015 Springer The original publication is available at www.springerlink.com |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Insight Centre for Data Analytics |
ID Code: | 20394 |
Deposited On: | 26 Mar 2015 14:03 by Dr. Kevin McGuinness . Last Modified 24 Jan 2019 15:50 |
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