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

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‐possib...

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Vydané v:Computer graphics forum Ročník 37; číslo 1; s. 32 - 44
Hlavní autori: Thiery, J.‐M., Eisemann, E.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Blackwell Publishing Ltd 01.02.2018
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ISSN:0167-7055, 1467-8659
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Shrnutí: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). 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).
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.13161