Natural Character Posing from a Large Motion Database

Xiaomao Wu 1 Maxime Tournier 2 Lionel Reveret 3
2 EVASION - Virtual environments for animation and image synthesis of natural objects
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
3 MORPHEO - Capture and Analysis of Shapes in Motion
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : An interactive inverse kinematics approach robustly generates natural poses in a large human-reachable space. It employs adaptive kd clustering to select a representative frame set from a large motion database and employs sparse approximation to accelerate training and posing. Model training is required only once. IK algorithms are fundamental in computer animation. However, designing energy functions that can generate natural poses for traditional IK algorithms is difficult. Style-based IK solves this problem by learning a prior model from motions. However, it might fail to generate natural poses when the desired poses differ considerably from the limited training poses. As we've shown, NAT-IK overcomes these limitations. It can relieve animators from time-consuming, back-and-forth, IK-pose adjustment. So, it's useful in automated applications such as games and virtual worlds
Type de document :
Article dans une revue
IEEE Computer Graphics and Applications, Institute of Electrical and Electronics Engineers, 2011, 31 (3), pp.69-77. 〈10.1109/MCG.2009.111〉
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https://hal.inria.fr/hal-00783123
Contributeur : Lionel Reveret <>
Soumis le : jeudi 31 janvier 2013 - 14:50:17
Dernière modification le : mercredi 11 avril 2018 - 01:59:31

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Xiaomao Wu, Maxime Tournier, Lionel Reveret. Natural Character Posing from a Large Motion Database. IEEE Computer Graphics and Applications, Institute of Electrical and Electronics Engineers, 2011, 31 (3), pp.69-77. 〈10.1109/MCG.2009.111〉. 〈hal-00783123〉

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