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Computer Vision in Sports pp 209–227Cite as

Classification of Sports Types Using Thermal Imagery

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

Abstract

In this chapter we propose a method for automatic classification of five different sports types. The approach is based only on occupancy heatmaps produced from position data and is robust to detection noise. To overcome privacy issues when capturing video in public sports arenas we use thermal imaging only. This image modality also facilitates easier detection of humans; the detection algorithm is based on automatic thresholding of the image. After a few occlusion handling procedures, the positions of people on the court are calculated using homography. Heatmaps are produced by summarising Gaussian distributions representing people over 10-minute periods. Before classification the heatmaps are projected to a low-dimensional discriminative space using the principle of Fisherfaces. We test our approach on 2 weeks of video and get promising results with a correct classification of 89.64 %. In addition, we get correct classification on a publicly available handball dataset.

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Authors and Affiliations

  1. Visual Analysis of People Lab, Aalborg University, Aalborg, Denmark

    Rikke Gade & Thomas B. Moeslund

Authors
  1. Rikke Gade
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  2. Thomas B. Moeslund
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Corresponding author

Correspondence to Rikke Gade .

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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Gade, R., Moeslund, T.B. (2014). Classification of Sports Types Using Thermal Imagery. 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_10

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  • DOI: https://doi.org/10.1007/978-3-319-09396-3_10

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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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