From Expressive End-Effector Trajectories to Expressive Bodily Motions *

Pamela Carreno-Medrano 1 Sylvie Gibet 1 Pierre-François Marteau 1
1 EXPRESSION - Expressiveness in Human Centered Data/Media
UBS - Université de Bretagne Sud, IRISA-D6 - MEDIA ET INTERACTIONS
Abstract : Recent results in the affective computing sciences point towards the importance of virtual characters capable of conveying affect through their movements. However, in spite of all advances made on the synthesis of expressive motions, almost all of the existing approaches focus on the translation of stylistic content rather than on the generation of new expressive motions. Based on studies that show the importance of end-effector trajectories in the perception and recognition of affect, this paper proposes a new approach for the automatic generation of affective motions. In this approach , expressive content is embedded in a low-dimensional manifold built from the observation of end-effector trajecto-ries. These trajectories are taken from an expressive motion capture database. Body motions are then reconstructed by a multi-chain Inverse Kinematics controller. The similarity between the expressive content of MoCap and synthesized motions is quantitatively assessed through information theory measures.
Type de document :
Communication dans un congrès
23rd International Conference on Computer Animation and Virtual World, May 2016, Genève, Switzerland. The 29th International Conference on Computer Animation and Social Agents CASA 2016, 〈10.1145/2915926.2915941〉
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https://hal.archives-ouvertes.fr/hal-01367822
Contributeur : Sylvie Gibet <>
Soumis le : mercredi 15 mars 2017 - 17:21:31
Dernière modification le : mercredi 7 février 2018 - 13:58:33

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Pamela Carreno-Medrano, Sylvie Gibet, Pierre-François Marteau. From Expressive End-Effector Trajectories to Expressive Bodily Motions *. 23rd International Conference on Computer Animation and Virtual World, May 2016, Genève, Switzerland. The 29th International Conference on Computer Animation and Social Agents CASA 2016, 〈10.1145/2915926.2915941〉. 〈hal-01367822〉

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