ラバン理論に基づいたヒューマンフォームロボット身体動作の動作特徴抽出と表出感情推定

概要

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A set of movement feature values, called a Labans feature value set, is proposed here in order to explain observers impression of bodily expression. The design concept of the Labans feature value set is based on Laban Movement Analysis (LMA), which is a proven theory in body movement psychology. In this paper, we adopt a Human Form Robot (HFR) as an agent of bodily expression because this is the type of a robot better adapted to Human-Agent Interaction (HAI). Relations between Labans feature values and HFRs emotions (Happy, Angry, Sad and Relaxation) which are the subjects of this study were examined using the analysis of correlations. By the consideration of Russells circumplex model of affect, we discussed the correlation in terms of each axial (“pleasure-displeasure” and “degree of arousal”) characteristics. Next, principal component analysis was conducted to examine multi-dimensional correlations. Finally four estimated emotion equations are generated by using the Labans features.