“Streamlining IBL workflows with computer vision and USD” by Cieri and Schwank
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Entry Number: 45
Title:
- Streamlining IBL workflows with computer vision and USD
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Abstract:
DNEG is constantly improving its global tools and processes to make them more efficient and artist-friendly, while leveraging state of-the-art technologies and trends in the industry. The special re quirements for Sony Pictures’ Venom movie were the perfect oppor tunity for us to improve our Image Based Lighting (IBL) workflows. In this paper we present the iblManager: a semi-automated sys tem to allow fast and artist-friendly extraction of numerous lights from HDR images (HDRIs), using computer vision. The system uses LightCache, a USD-based implementation of light descriptions, to allow cross-DCC usage and pipeline integration.
References:
Paul Debevec. 2006. A Median Cut Algorithm for Light Probe Sampling. In ACM SIGGRAPH 2006 Courses (SIGGRAPH ’06). ACM, New York, NY, USA, Article 6. https://doi.org/10.1145/1185657.1185688
Tadao Mihashi, Dan Abrams, Paul Lambert, Marco Maldonado, and Jesse James Chisholm. 2009. The Light Kit: HDRI-Based Area Light System for “The Curi ous Case of Benjamin Button”. In SIGGRAPH 2009 Talks: Two Bolts and a Button.
Ben Snow. 2010. Terminators and Iron Men: Image-Based Lighting and Physical Shading at ILM. In SIGGRAPH 2010 Course: Physically Based Shading Models in Film and Game Production.
Alex Suter, Dan Lobl, Victor Schutz, and Brian Gee. 2016. LightCraft: Extract Light Position and Information from On-set Photography. In ACM SIGGRAPH 2016 Talks (SIGGRAPH ’16). ACM, New York, NY, USA, Article 15, 2 pages. https://doi.org/10. 1145/2897839.2927464
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Acknowledgements:
We thank Bernardo Spadafora for his key contribution to the tool development; Ignacio Thomas, Sachin Narendra for their precious input. A big thank you goes to Matthew Smith, Bernhard Ker schbaumer, Mark Pascoe and to our colleagues, especially Keanan Cantrell, Alison Wortman, Peter Seager, Tom Bracht.