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, S.; Niewiadomski, R.; Volpe, G.; Alborno, P.; Mancini, M.; Camurri, A.. - ELETTRONICO. - (2016), pp. 1629-1636. (Intervento presentato al convegno 34th Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2016 tenutosi a San Jose Convention Center, usa nel 2016) [10.1145/2851581.2892478].
Movement fluidity analysis based on performance and perception
Niewiadomski R.;
2016-01-01
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.File | Dimensione | Formato | |
---|---|---|---|
CHI2016_pianaetal.pdf
Solo gestori archivio
Tipologia:
Post-print referato (Refereed author’s manuscript)
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
259.17 kB
Formato
Adobe PDF
|
259.17 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione