End-effectors trajectories: An efficient low-dimensional characterization of affective-expressive body motions - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2015

End-effectors trajectories: An efficient low-dimensional characterization of affective-expressive body motions

Résumé

Virtual characters capable of showing emotional content are considered as more believable and engaging. However, in spite of the numerous psychological studies and machine learning applications trying to decode the most salient features in the expression and perception of affect, there is still no common understanding about how affect is conveyed through body motions. Based on findings reported by the psychology research community and quantitative results obtained in the computer animation domain during the last years, we propose to represent affective bodily movement through a low-dimensional parameterization consisting of the spatio-temporal trajectories of eight main joints in the human body (hands, head, feet, elbows and pelvis). Using a combined evaluation protocol, we show that this low-dimensional parameterization and the features derived from it are a compact and sufficient representation of affective motions that can be used for automatic recognition of affect and the generation of new affective-expressive motions.
Fichier non déposé

Dates et versions

hal-01367814 , version 1 (16-09-2016)

Identifiants

Citer

Pamela Carreno-Medrano, Sylvie Gibet, Pierre-François Marteau. End-effectors trajectories: An efficient low-dimensional characterization of affective-expressive body motions. International Conference on Affective Computing and Intelligent Interaction, Sep 2015, Xian, China. ⟨10.1109/ACII.2015.7344607⟩. ⟨hal-01367814⟩
293 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More