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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