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Multi-weight enveloping: least-squares approximation techniques for skin animation

Published: 21 July 2002 Publication History

Abstract

We present a process called multi-weight enveloping for deforming the skin geometry of the body of a digital creature around its skeleton. It is based on a deformation equation whose coefficients we compute using a statistical fit to an input training exercise. In this input, the skeleton and the skin move together, by arbitrary external means, through a range of motion representative of what the creature is expected to achieve in practice. The input can also come from existing pieces of handcrafted skin animation. Using a modified least-squares fitting technique, we compute the coefficients, or "weights", of the deformation equation. The result is that the equation generalizes the skin movement so that it applies well to other sequences of animation. The multi-weight deformation equation is computationally efficient to evaluate; once the training process is complete, even creatures with high levels of geometric detail can move at interactive frames rates with a look that approximates that of anatomical, physically-based models. We demonstrate the technique in a feature film production environment, on a human model whose input poses are sculpted by hand and an animal model whose input poses come from the output of an anatomically-based dynamic simulation.

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cover image ACM Conferences
SCA '02: Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
July 2002
203 pages
ISBN:1581135734
DOI:10.1145/545261
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 21 July 2002

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Author Tags

  1. enveloping
  2. skinning
  3. surface deformation

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SCA02
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SCA02: Symposium on Computer Animation
July 21 - 22, 2002
Texas, San Antonio

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SCA '02 Paper Acceptance Rate 22 of 53 submissions, 42%;
Overall Acceptance Rate 183 of 487 submissions, 38%

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Cited By

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  • (2023)GSNet: Generating 3D garment animation via graph skinning networkGraphical Models10.1016/j.gmod.2023.101197129(101197)Online publication date: Oct-2023
  • (2023)PGN-Cloth: Physics-based graph network model for 3D cloth animationDisplays10.1016/j.displa.2023.10253480(102534)Online publication date: Dec-2023
  • (2022)CASAProceedings of the 36th International Conference on Neural Information Processing Systems10.5555/3600270.3602340(28559-28574)Online publication date: 28-Nov-2022
  • (2021)PBNSACM Transactions on Graphics10.1145/3478513.348047940:6(1-14)Online publication date: 10-Dec-2021
  • (2021)Learning skeletal articulations with neural blend shapesACM Transactions on Graphics10.1145/3450626.345985240:4(1-15)Online publication date: 19-Jul-2021
  • (2021)Velocity Skinning for Real‐time Stylized Skeletal AnimationComputer Graphics Forum10.1111/cgf.14265440:2(549-561)Online publication date: 4-Jun-2021
  • (2021)SNARF: Differentiable Forward Skinning for Animating Non-Rigid Neural Implicit Shapes2021 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV48922.2021.01139(11574-11584)Online publication date: Oct-2021
  • (2021)DeePSD: Automatic Deep Skinning And Pose Space Deformation For 3D Garment Animation2021 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV48922.2021.00542(5451-5460)Online publication date: Oct-2021
  • (2021)LEAP: Learning Articulated Occupancy of People2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR46437.2021.01032(10456-10466)Online publication date: Jun-2021
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