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Modular Scene Filtering via the Pixar Hydra 2.0 Architecture

Published:24 July 2022Publication History

ABSTRACT

Pixar’s Hydra project began as an abstract scene interface to an OpenGL-based renderer intended for interactive viewports across multiple applications. As the project added integrations with other renderers (including path tracers), it became clear that it needed a richer scene interface to convey a broader set of renderer features, as well as a more structured and modular way to resolve the scene into rendering primitives.

We’ll discuss the Hydra 2.0 architecture that was developed to address this problem, with examples from two scene filtering cases:

References

  1. George Elkoura, Sebastian Grassia, Sunya Boonyatera, Alex Mohr, Pol Jeremias-Vila, and Matt Kuruc. 2019. A Deep Dive into Universal Scene Description and Hydra. In ACM SIGGRAPH 2019 Courses (Los Angeles, California) (SIGGRAPH ’19). Association for Computing Machinery, New York, NY, USA, Article 1, 48 pages. https://doi.org/10.1145/3305366.3328033Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Academy Software Foundation. 2022a. MaterialX. https://www.materialx.org/.Google ScholarGoogle Scholar
  3. Academy Software Foundation. 2022b. Open Shading Language. http://openshadinglanguage.org/.Google ScholarGoogle Scholar
  4. Florian Hecht, Daniel McCoy, Stephen LaVietes, and F. Sebastian Grassia. 2021. UsdShade in the Pixar Pipeline. In ACM SIGGRAPH 2021 Talks (Virtual Event, USA) (SIGGRAPH ’21). Association for Computing Machinery, New York, NY, USA, Article 5, 2 pages. https://doi.org/10.1145/3450623.3464670Google ScholarGoogle ScholarDigital LibraryDigital Library

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  • Published in

    cover image ACM Conferences
    SIGGRAPH '22: ACM SIGGRAPH 2022 Talks
    July 2022
    108 pages
    ISBN:9781450393713
    DOI:10.1145/3532836

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 24 July 2022

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    • invited-talk
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    • Refereed limited

    Acceptance Rates

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

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