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A multi-modal dance corpus for research into interaction between humans in virtual environments

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Abstract

We present a new, freely available, multimodal corpus for research into, amongst other areas, real-time realistic interaction between humans in online virtual environments. The specific corpus scenario focuses on an online dance class application scenario where students, with avatars driven by whatever 3D capture technology is locally available to them, can learn choreographies with teacher guidance in an online virtual dance studio. As the dance corpus is focused on this scenario, it consists of student/teacher dance choreographies concurrently captured at two different sites using a variety of media modalities, including synchronised audio rigs, multiple cameras, wearable inertial measurement devices and depth sensors. In the corpus, each of the several dancers performs a number of fixed choreographies, which are graded according to a number of specific evaluation criteria. In addition, ground-truth dance choreography annotations are provided. Furthermore, for unsynchronised sensor modalities, the corpus also includes distinctive events for data stream synchronisation. The total duration of the recorded content is 1 h and 40 min for each single sensor, amounting to 55 h of recordings across all sensors. Although the dance corpus is tailored specifically for an online dance class application scenario, the data is free to download and use for any research and development purposes.

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Notes

  1. More ratings by other experienced Salsa dancers will be provided in the near future

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Acknowledgments

The authors and 3DLife would like to acknowledge the support of Huawei in the creation of this dataset. In addition, warmest thanks go to all the contributors to these capture sessions, especially: The Dancers Anne-Sophie K., Anne-Sophie M., Bertrand, Gabi, Gael, Habib, Helene, Jacky, Jean-Marc, Laetitia, Martine, Ming-Li, Remi, Roland, Thomas. The Tech Guys Alfred, Dave, Dominique, Fabrice, Gael, Georgios, Gilbert, Marc, Mounira, Noel, Phil, Radek, Robin, Slim, Qianni, Sophie-Charlotte, Thomas, Xinyu, Yves. This research was partially supported by the European Commission under contract FP7-247688 3DLife.

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Authors and Affiliations

  1. Institut Telecom/Telecom ParisTech, CNRS-LTCI, Paris, France

    Slim Essid, Thomas Fillon, Alfred Dielmann, Robin Tournemenne, Aymeric Masurelle & Gaël Richard

  2. Multimedia and Vision Group (MMV), Queen Mary University, London, UK

    Xinyu Lin, Georgios Kordelas, Anil Aksay, Qianni Zhang, Vlado Kitanovski & Ebroul Izquierdo

  3. CLARITY, Centre for Sensor Web Technologies, Dublin City University, Dublin, Ireland

    Marc Gowing, Philip Kelly & Noel E. O’Connor

  4. Centre for Research and Technology-Hellas, Informatics and Telematics Institute, Thessaloníki, Greece

    Georgios Kordelas & Petros Daras

Authors
  1. Slim Essid
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  2. Xinyu Lin
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  3. Marc Gowing
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  4. Georgios Kordelas
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  6. Philip Kelly
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  7. Thomas Fillon
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  8. Qianni Zhang
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  9. Alfred Dielmann
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  10. Vlado Kitanovski
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  11. Robin Tournemenne
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  12. Aymeric Masurelle
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  13. Ebroul Izquierdo
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  14. Noel E. O’Connor
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  15. Petros Daras
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  16. Gaël Richard
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Corresponding author

Correspondence to Slim Essid.

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Essid, S., Lin, X., Gowing, M. et al. A multi-modal dance corpus for research into interaction between humans in virtual environments. J Multimodal User Interfaces 7, 157–170 (2013). https://doi.org/10.1007/s12193-012-0109-5

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  • DOI: https://doi.org/10.1007/s12193-012-0109-5

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