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Project deliverable . 2017
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WhoLoDancE: Deliverable 3.4 - Report on multimodal signal modelling

Authors: Piana, Stefano; Camurri, Antonio;

WhoLoDancE: Deliverable 3.4 - Report on multimodal signal modelling

Abstract

{"references": ["Camurri, A., Krumhansl, C. L., Mazzarino, B., & Volpe, G. (2004). An exploratory study of anticipating human movement in dance. the Proceedings of this same Conference.", "Glowinski, D., Dael, N., Camurri, A., Volpe, G., Mortillaro, M., & Scherer, K. (2011). Toward a minimal representation of affective gestures. IEEE Transactions on Affective Computing, 2, 106-118.", "Glowinski, D., Gnecco, G., Piana, S., & Camurri, A. (2013). Expressive non-verbal interaction in string quartet. Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on, (pp. 233-238).", "Kleinsmith, A., & Bianchi-Berthouze, N. (2013). Affective body expression perception and recognition: A survey. IEEE Transactions on Affective Computing, 4, 15-33.", "Piana, S., Staglian\u00f2, A., Odone, F., & Camurri, A. (2016). Adaptive body gesture representation for automatic emotion recognition. ACM Transactions on Interactive Intelligent Systems (TiiS), 6, 6.", "Richman, J. S., & Moorman, J. R. (2000). Physiological time-series analysis using approximate entropy and sample entropy. American Journal of Physiology-Heart and Circulatory Physiology, 278, H2039--H2049."]}

This deliverable serves to summarize the input devices, data formats and methodologies adopted in the process of developing algorithms, software modules and applications for movement principle and qualities analysis. Section 1 introduces the report and lists its objectives whereas Section 2 gives an overview of the data capture systems that are used in the context of the project; in particular, a description of professional motion capture systems, used during the production of the WhoLoDancE repository, and low-end capture devices, that are used in the low-cost applications, is given. Section 3 introduces the methodology followed in the design and development of movement analysis algorithm and software modules, in particular, a conceptual framework is described where the qualities of movement are organized in a hierarchical way, going from physical signals to abstract, complex concepts.

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Keywords

data, analysis, framework, multimodal

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