WhoLoDancE: Deliverable 3.5 - Report on data-driven and model-driven analysis methodologies
| Autor: | Camurri, Antonio, Piana, Stefano, Alborno, Paolo, Kolykhalova, Ksenia, De Giorgis, Nikolas, Buccoli, Michele, Zanoni, Massimiliano |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| DOI: | 10.5281/zenodo.1135188 |
| Popis: | This deliverable summarizes the description of the development of techniques adopted for multimodal analysis of dance at both individual and group levels, data-driven, and model-driven analysis. Section 1 introduces the report and lists its objectives whereas Section 2 refers to the methodology employed in the data-driven approach. Section 3 provides an overview of developed model-driven approaches to extract movement dimensions related to the dance-learning scenario: from low-level model-based movement dimension to more complex intra- and inter- network related methodologies, including a technique to automatically segment dance sequences in meaningful chunks. {"references":["Camurri, A. G. (2016). The dancer in the eye: towards a multi-layered computational framework of qualities in movement. Proceedings of the 3rd International Symposium on Movement and Computing. ACM.","Phillips-Silver, J. a. (2012). Searching for roots of entrainment and joint action in early musical interactions. Frontiers in human neuroscience.","Quiroga, R. Q. (2002). Event synchronization: a simple and fast method to measure synchronicity and time delay patterns. Physical review."]} |
| Databáze: | OpenAIRE |
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