A. Camurri, K. E. Raheb, O. Even-Zohar, Y. Ioannidis, Amalia Markatzi, Jean-Marc Matos, E. Morley-Fletcher, Pablo Palacio, M. Romero, A. Sarti, S. Pietro, Vladimir Viro, Sarah Whatley
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WhoLoDancE: Towards a methodology for selecting Motion Capture Data across different Dance Learning Practice
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.