WhoLoDancE: Towards a methodology for selecting Motion Capture Data across different Dance Learning Practice

A. Camurri, K. El Raheb, O. Even-Zohar, Y. Ioannidis, A. Markatzi, J.-M. Matos, E. Morley-Fletcher, P. Palacio, M. Romero, A. Sarti, S. Di Pietro, V. Viro, Sarah Whatley

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

6 Citations (Scopus)

Abstract

In this paper we present the objectives and preliminary work of WhoLoDancE a Research and Innovation Action funded under the European Union's Horizon 2020 programme, aiming at using new technologies for capturing and analyzing dance movement to facilitate whole-body interaction learning experiences for a variety of dance genres. Dance is a diverse and heterogeneous practice and WhoLoDancE will develop a protocol for the creation and/or selection of dance sequences drawn from different dance styles for different teaching and learning modalities. As dance learning practice lacks standardization beyond dance genres and specific schools and techniques, one of the first project challenges is to bring together a variety of dance genres and teaching practices and work towards a methodology for selecting the appropriate shots for motion capturing, to acquire kinetic material which will provide a satisfying proof of concept for Learning scenarios of particular genres. The four use cases we are investigating are 1) classical ballet, 2) contemporary dance, 3) flamenco and 4) Greek folk dance.
LanguageEnglish
Title of host publicationMOCO '16 Proceedings of the 3rd International Symposium on Movement and Computing
Place of PublicationNew York
PublisherACM
ISBN (Print)978-1-4503-4307-7
DOIs
Publication statusPublished - 2016
EventInternational Symposium on Movement and Computing - Thessaloniki, Greece
Duration: 5 Jul 20167 Jul 2016

Conference

ConferenceInternational Symposium on Movement and Computing
CountryGreece
CityThessaloniki
Period5/07/167/07/16

Fingerprint

Data acquisition
Teaching
Standardization
Innovation
Kinetics
European Union

Bibliographical note

© ACM 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in MOCO '16 Proceedings of the 3rd International Symposium on Movement and Computing, http://dx.doi.org/10.1145/2948910.2948912

Keywords

  • Dance Learning
  • Motion Capture
  • Human Movement
  • Whole-Body interaction
  • Dance practices and genres

Cite this

Camurri, A., El Raheb, K., Even-Zohar, O., Ioannidis, Y., Markatzi, A., Matos, J-M., ... Whatley, S. (2016). WhoLoDancE: Towards a methodology for selecting Motion Capture Data across different Dance Learning Practice. In MOCO '16 Proceedings of the 3rd International Symposium on Movement and Computing [43] New York: ACM. https://doi.org/10.1145/2948910.2948912

WhoLoDancE: Towards a methodology for selecting Motion Capture Data across different Dance Learning Practice. / Camurri, A.; El Raheb, K.; Even-Zohar, O.; Ioannidis, Y.; Markatzi, A.; Matos, J.-M.; Morley-Fletcher, E.; Palacio, P.; Romero, M.; Sarti, A.; Di Pietro, S.; Viro, V.; Whatley, Sarah.

MOCO '16 Proceedings of the 3rd International Symposium on Movement and Computing. New York : ACM, 2016. 43.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Camurri, A, El Raheb, K, Even-Zohar, O, Ioannidis, Y, Markatzi, A, Matos, J-M, Morley-Fletcher, E, Palacio, P, Romero, M, Sarti, A, Di Pietro, S, Viro, V & Whatley, S 2016, WhoLoDancE: Towards a methodology for selecting Motion Capture Data across different Dance Learning Practice. in MOCO '16 Proceedings of the 3rd International Symposium on Movement and Computing., 43, ACM, New York, International Symposium on Movement and Computing, Thessaloniki, Greece, 5/07/16. https://doi.org/10.1145/2948910.2948912
Camurri A, El Raheb K, Even-Zohar O, Ioannidis Y, Markatzi A, Matos J-M et al. WhoLoDancE: Towards a methodology for selecting Motion Capture Data across different Dance Learning Practice. In MOCO '16 Proceedings of the 3rd International Symposium on Movement and Computing. New York: ACM. 2016. 43 https://doi.org/10.1145/2948910.2948912
Camurri, A. ; El Raheb, K. ; Even-Zohar, O. ; Ioannidis, Y. ; Markatzi, A. ; Matos, J.-M. ; Morley-Fletcher, E. ; Palacio, P. ; Romero, M. ; Sarti, A. ; Di Pietro, S. ; Viro, V. ; Whatley, Sarah. / WhoLoDancE: Towards a methodology for selecting Motion Capture Data across different Dance Learning Practice. MOCO '16 Proceedings of the 3rd International Symposium on Movement and Computing. New York : ACM, 2016.
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