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Efficient multiple scattering in hair using spherical harmonics

Published: 01 August 2008 Publication History

Abstract

Previous research has shown that a global multiple scattering simulation is needed to achieve physically realistic renderings of hair, particularly light-colored hair with low absorption. However, previous methods have either sacrificed accuracy or have been too computationally expensive for practical use. In this paper we describe a physically based, volumetric rendering method that computes multiple scattering solutions, including directional effects, much faster than previous accurate methods. Our two-pass method first traces light paths through a volumetric representation of the hair, contributing power to a 3D grid of spherical harmonic coefficients that store the directional distribution of scattered radiance everywhere in the hair volume. Then, in a ray tracing pass, multiple scattering is computed by integrating the stored radiance against the scattering functions of visible fibers using an efficient matrix multiplication. Single scattering is computed using conventional direct illumination methods. In our comparisons the new method produces quality similar to that of the best previous methods, but computes multiple scattering more than 10 times faster.

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Published In

cover image ACM Transactions on Graphics
ACM Transactions on Graphics  Volume 27, Issue 3
August 2008
844 pages
ISSN:0730-0301
EISSN:1557-7368
DOI:10.1145/1360612
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 August 2008
Published in TOG Volume 27, Issue 3

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Author Tags

  1. hair
  2. multiple scattering
  3. spherical harmonics

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Cited By

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  • (2023)Deep Appearance PrefilteringACM Transactions on Graphics10.1145/357032742:2(1-23)Online publication date: 16-Jan-2023
  • (2023)Accelerating Hair Rendering by Learning High‐Order Scattered RadianceComputer Graphics Forum10.1111/cgf.1489542:4Online publication date: 26-Jul-2023
  • (2022)Practical level-of-detail aggregation of fur appearanceACM Transactions on Graphics10.1145/3528223.353010541:4(1-17)Online publication date: 22-Jul-2022
  • (2022)A deep learning‐based framework for fast generation of photorealistic hair animationsIET Image Processing10.1049/ipr2.1263817:2(375-387)Online publication date: 30-Sep-2022
  • (2021)A GAN-based temporally stable shading model for fast animation of photorealistic hairComputational Visual Media10.1007/s41095-020-0201-97:1(127-138)Online publication date: 18-Jan-2021
  • (2020)Survey of Models for Acquiring the Optical Properties of Translucent MaterialsComputer Graphics Forum10.1111/cgf.1402339:2(729-755)Online publication date: 13-Jul-2020
  • (2020)WISH: efficient 3D biological shape classification through Willmore flow and Spherical Harmonics decomposition2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW50498.2020.00494(4184-4194)Online publication date: Jun-2020
  • (2020)Neural Hair RenderingComputer Vision – ECCV 202010.1007/978-3-030-58523-5_22(371-388)Online publication date: 23-Aug-2020
  • (2019)Constant-Error Pseudorandomness Proofs from Hardness Require MajorityACM Transactions on Computation Theory10.1145/332281511:4(1-11)Online publication date: 17-Jun-2019
  • (2018)Analysis of Hair Shine Using Rendering and Subjective EvaluationACM Transactions on Applied Perception10.1145/327447815:4(1-17)Online publication date: 1-Oct-2018
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