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Bodyopt - A Character Deformation Pipeline For Avatar: The Way of Water

Published:07 August 2023Publication History

ABSTRACT

We present Bodyopt, a character skin deformation framework developed for Avatar: The Way of Water. Our approach aims to learn the skin deformations from a given dataset and reproduce them reliably during shot production. In conjunction with the kinematic skeleton, we employ muscle fibers as an additional anatomical basis, where their length changes serve as a parametrization for the non-linear deformation components. We provide a novel way of curating the dataset to minimizing differences between similar poses, which would otherwise lead to a quality loss in the reconstruction. Our approach also handles runtime skin dynamics and utilities for artists to transfer deformations to new character types as well as extra modifiers for secondary motions like breathing. Additionally, we close the gap between final skin deformation and the representation used in Animation by providing a fast proxy solution that is based on the same input data.

References

  1. Byungkuk Choi, Haekwang Eom, Benjamin Mouscadet, Stephen Cullingford, Kurt Ma, Stefanie Gassel, Suzi Kim, Andrew Moffat, Millicent Maier, Marco Revelant, Joe Letteri, and Karan Singh. 2022. Animatomy: an Animator-centric, Anatomically Inspired System for 3D Facial Modeling, Animation and Transfer. SA ’22: SIGGRAPH Asia 2022 Conference Papers 16 (2022), 1–9.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Binh Huy Le and J P Lewis. 2019. Direct delta mush skinning and variants. ACM Trans. Graph 38, 113 (2019), 1–13.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Robert W. Sumner and Jovan Popović. 2004. Deformation transfer for triangle meshes. ACM Trans. Graph 23, 3 (2004), 399–405.Google ScholarGoogle ScholarDigital LibraryDigital Library

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        • Published in

          cover image ACM Conferences
          SIGGRAPH '23: ACM SIGGRAPH 2023 Talks
          August 2023
          147 pages
          ISBN:9798400701436
          DOI:10.1145/3587421

          Copyright © 2023 Owner/Author

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 7 August 2023

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          • invited-talk
          • Research
          • Refereed limited

          Acceptance Rates

          Overall Acceptance Rate1,822of8,601submissions,21%

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          SIGGRAPH '24
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