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Optimizing rig manipulation with GPU and parallel evaluation

Published:28 July 2019Publication History

ABSTRACT

Rig speed plays a critical role in animation pipelines. Real-time performance provides instant feedback to artists, thereby allowing quick iterations and ultimately leading to better quality animation. A complete approach to real-time performance requires both playback and manipulation at interactive speeds. A pose-based caching system (PBCS) addresses the former, but the manipulation of complex rigs remains slow. This paper speeds up rig manipulation by taking advantage of modern multi-core architectures and the GPU, and by constructing rigs that evaluate efficiently on parallel processing hardware. This complete approach, including tool updates and rig optimizations, was used successfully to significantly improve interactive rig manipulation performance on Frozen 2.

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References

  1. Autodesk. 2016. Maya. (2016). https://www.autodesk.com/products/mayaGoogle ScholarGoogle Scholar
  2. Andy Lin, Gene S. Lee, Joe Longson, Jay Steele, Evan Goldberg, and Rastko Stefanovic. 2015. Achieving Real-time Playback with Production Rigs. In ACM SIGGRAPH 2015 Talks (SIGGRAPH '15). ACM, New York, NY, USA, Article 11, 1 pages. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Conferences
      SIGGRAPH '19: ACM SIGGRAPH 2019 Talks
      July 2019
      143 pages
      ISBN:9781450363174
      DOI:10.1145/3306307

      Copyright © 2019 Owner/Author

      Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 28 July 2019

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