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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, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
3 MORPHEO - Capture and Analysis of Shapes in Motion
Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann, Inria Grenoble - Rhône-Alpes
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
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Submitted on : Thursday, January 31, 2013 - 2:50:17 PM
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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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