ARAPLBS: Robust and Efficient Elasticity‐Based Optimization of Weights and Skeleton Joints for Linear Blend Skinning with Parametrized Bones

ARAPLBS: Robust and Efficient Elasticity‐Based Optimization of Weights and Skeleton Joints for... We present a fast, robust and high‐quality technique to skin a mesh with reference to a skeleton. We consider the space of possible skeleton deformations (based on skeletal constraints, or skeletal animations), and compute skinning weights based on an optimization scheme to obtain as‐rigid‐as‐possible (ARAP) corresponding mesh deformations. We support stretchable‐and‐twistable bones (STBs) and spines by generalizing the ARAP deformations to stretchable deformers. In addition, our approach can optimize joint placements. If wanted, a user can guide and interact with the results, which is facilitated by an interactive feedback, reached via an efficient sparsification scheme. We demonstrate our technique on challenging inputs (STBs and spines, triangle and tetrahedral meshes featuring missing elements, boundaries, self‐intersections or wire edges). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computer Graphics Forum Wiley

ARAPLBS: Robust and Efficient Elasticity‐Based Optimization of Weights and Skeleton Joints for Linear Blend Skinning with Parametrized Bones

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
© 2018 The Eurographics Association and John Wiley & Sons Ltd.
ISSN
0167-7055
eISSN
1467-8659
D.O.I.
10.1111/cgf.13161
Publisher site
See Article on Publisher Site

Abstract

We present a fast, robust and high‐quality technique to skin a mesh with reference to a skeleton. We consider the space of possible skeleton deformations (based on skeletal constraints, or skeletal animations), and compute skinning weights based on an optimization scheme to obtain as‐rigid‐as‐possible (ARAP) corresponding mesh deformations. We support stretchable‐and‐twistable bones (STBs) and spines by generalizing the ARAP deformations to stretchable deformers. In addition, our approach can optimize joint placements. If wanted, a user can guide and interact with the results, which is facilitated by an interactive feedback, reached via an efficient sparsification scheme. We demonstrate our technique on challenging inputs (STBs and spines, triangle and tetrahedral meshes featuring missing elements, boundaries, self‐intersections or wire edges).

Journal

Computer Graphics ForumWiley

Published: Jan 1, 2018

Keywords: ; ; ; ; ;

References

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