In this work we present a framework and an experimental approach to investigate human body movement qualities (i.e., the expressive components of non-verbal communication) in HCI. We first define a candidate movement quality conceptually, with the involvement of experts in the field (e.g., dancers, choreographers). Next, we collect a dataset of performances and we evaluate the perception of the chosen quality. Finally, we propose a computational model to detect the presence of the quality in a movement segment and we compare the outcomes of the model with the evaluation results. In the proposed on-going work, we apply this approach to a specific quality of movement: Fluidity. The proposed methods and models may have several applications, e.g., in emotion detection from full-body movement, interactive training of motor skills, rehabilitation.

Movement Fluidity Analysis Based on Performance and Perception / Piana, Stefano; Alborno, Paolo; Niewiadomski, Radoslaw; Mancini, Maurizio; Volpe, Gualtiero; Camurri, Antonio. - (2016), pp. 1629-1636. (Intervento presentato al convegno the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems tenutosi a San Jose, CA) [10.1145/2851581.2892478].

Movement Fluidity Analysis Based on Performance and Perception

MANCINI, MAURIZIO;VOLPE, GUALTIERO;
2016

Abstract

In this work we present a framework and an experimental approach to investigate human body movement qualities (i.e., the expressive components of non-verbal communication) in HCI. We first define a candidate movement quality conceptually, with the involvement of experts in the field (e.g., dancers, choreographers). Next, we collect a dataset of performances and we evaluate the perception of the chosen quality. Finally, we propose a computational model to detect the presence of the quality in a movement segment and we compare the outcomes of the model with the evaluation results. In the proposed on-going work, we apply this approach to a specific quality of movement: Fluidity. The proposed methods and models may have several applications, e.g., in emotion detection from full-body movement, interactive training of motor skills, rehabilitation.
2016
the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems
movement; analysis; Fluidity; perception; evaluation; performance; dance.
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Movement Fluidity Analysis Based on Performance and Perception / Piana, Stefano; Alborno, Paolo; Niewiadomski, Radoslaw; Mancini, Maurizio; Volpe, Gualtiero; Camurri, Antonio. - (2016), pp. 1629-1636. (Intervento presentato al convegno the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems tenutosi a San Jose, CA) [10.1145/2851581.2892478].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1528265
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