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Real-Time Event Detection in Field Sport Videos

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Computer Vision in Sports

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

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.

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Author information

Authors and Affiliations

  1. Faculty of Computing, ul. Piotrowo 3A, Poznan, Poland

    Rafal Kapela & Aleksandra Swietlicka

  2. Insight Centre for Data Analytics, Dublin City University, Glasnevin, Dublin 9, Ireland

    Kevin McGuinness & Noel E. O’Connor

Authors
  1. Rafal Kapela
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  2. Kevin McGuinness
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  3. Aleksandra Swietlicka
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  4. Noel E. O’Connor
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Corresponding author

Correspondence to Rafal Kapela .

Editor information

Editors and Affiliations

  1. Aalborg University, Aalborg, Denmark

    Thomas B. Moeslund

  2. BBC R&D, London, United Kingdom

    Graham Thomas

  3. University of Surrey, Guildford, Surrey, United Kingdom

    Adrian Hilton

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© 2014 Springer International Publishing Switzerland

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Kapela, R., McGuinness, K., Swietlicka, A., O’Connor, N.E. (2014). Real-Time Event Detection in Field Sport Videos. In: Moeslund, T., Thomas, G., Hilton, A. (eds) Computer Vision in Sports. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-09396-3_14

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  • DOI: https://doi.org/10.1007/978-3-319-09396-3_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09395-6

  • Online ISBN: 978-3-319-09396-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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