Perception based real-time dynamic adaptation of human motions

Ludovic Hoyet 1 Franck Multon 1, 2 Taku Komura 3 Anatole Lécuyer 1
1 BUNRAKU - Perception, decision and action of real and virtual humans in virtual environments and impact on real environments
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, ENS Cachan - École normale supérieure - Cachan, Inria Rennes – Bretagne Atlantique
Abstract : This paper presents a new real-time method for dynamics-based animation of virtual characters. It is based on rough physical approximations that lead to natural-looking and physically realistic human motions. The first part of this work consists in evaluating the relevant parameters of natural motions performed by people subject to various external perturbations. According to this pilot study, we have defined a method that is able to adapt in real-time the motion of a virtual character in order to satisfy kinematic and dynamic constraints, such as pushing, pulling and carrying objects with more or less mass. This method relies on laws provided by experimental studies that enable us to avoid using complex mechanical models and thus save computation time. One of the most important assumption consists in decoupling the pose of character and the timing of the motion. Thanks to this method, it is possible to animate up to 15 characters at 60Hz while dealing with complex kinematic and dynamic constraints.
Type de document :
Communication dans un congrès
Motion in Games, Nov 2010, Zeist, Netherlands. Springer Berlin / Heidelberg, 6459, pp.266-277, 2010, Lecture Notes in Computer Science. 〈10.1007/978-3-642-16958-8_25〉
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https://hal.inria.fr/inria-00535979
Contributeur : Ludovic Hoyet <>
Soumis le : dimanche 14 novembre 2010 - 18:49:41
Dernière modification le : mercredi 16 mai 2018 - 11:23:18

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Ludovic Hoyet, Franck Multon, Taku Komura, Anatole Lécuyer. Perception based real-time dynamic adaptation of human motions. Motion in Games, Nov 2010, Zeist, Netherlands. Springer Berlin / Heidelberg, 6459, pp.266-277, 2010, Lecture Notes in Computer Science. 〈10.1007/978-3-642-16958-8_25〉. 〈inria-00535979〉

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