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International Conference on Business Information Systems

BIS 2020: Business Information Systems pp 118–129Cite as

Computer Vision for the Ballet Industry: A Comparative Study of Methods for Pose Recognition

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 389))

Abstract

The presence of computer vision technology is continually expanding into multiple application domains. An industry and an art form that is particularly attractive for the application of computer vision algorithms is ballet. Due to the well-codified poses, along with the challenges that exist within the ballet domain, automation for the ballet environment is a relevant research problem. The paper proposes a model called BaReCo, which allows for ballet poses to be recognised using computer vision methods. The model contains multiple computer vision pipelines which allows for the comparison of approaches that have not been widely explored in the ballet domain. The results have shown that the top-performing pipelines achieved an accuracy rate of 99.375% and an Equal Error Rate (EER) of 0.119% respectively. The study additionally produced a ballet pose dataset, which serves as a contribution to the ballet and computer vision community. By combining suitable computer vision methods, the study demonstrates that successful recognition of ballet poses can be accomplished.

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Acknowledgements

This research benefitted, in part, from support from the Faculty of Science at the University of Johannesburg.

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Authors and Affiliations

  1. University of Johannesburg, Kingsway Avenue and University Rds, Auckland Park, Johannesburg, South Africa

    Margaux Fourie & Dustin van der Haar

Authors
  1. Margaux Fourie
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  2. Dustin van der Haar
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Corresponding authors

Correspondence to Margaux Fourie or Dustin van der Haar .

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Editors and Affiliations

  1. Poznań University of Economics and Business, Poznan, Poland

    Witold Abramowicz

  2. University of Colorado, Colorado Springs, CO, USA

    Gary Klein

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Fourie, M., van der Haar, D. (2020). Computer Vision for the Ballet Industry: A Comparative Study of Methods for Pose Recognition. In: Abramowicz, W., Klein, G. (eds) Business Information Systems. BIS 2020. Lecture Notes in Business Information Processing, vol 389. Springer, Cham. https://doi.org/10.1007/978-3-030-53337-3_9

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  • DOI: https://doi.org/10.1007/978-3-030-53337-3_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-53336-6

  • Online ISBN: 978-3-030-53337-3

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