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Clustered principal components for precomputed radiance transfer

Published: 01 July 2003 Publication History

Abstract

We compress storage and accelerate performance of precomputed radiance transfer (PRT), which captures the way an object shadows, scatters, and reflects light. PRT records over many surface points a transfer matrix. At run-time, this matrix transforms a vector of spherical harmonic coefficients representing distant, low-frequency source lighting into exiting radiance. Per-point transfer matrices form a high-dimensional surface signal that we compress using clustered principal component analysis (CPCA), which partitions many samples into fewer clusters each approximating the signal as an affine subspace. CPCA thus reduces the high-dimensional transfer signal to a low-dimensional set of per-point weights on a per-cluster set of representative matrices. Rather than computing a weighted sum of representatives and applying this result to the lighting, we apply the representatives to the lighting per-cluster (on the CPU) and weight these results per-point (on the GPU). Since the output of the matrix is lower-dimensional than the matrix itself, this reduces computation. We also increase the accuracy of encoded radiance functions with a new least-squares optimal projection of spherical harmonics onto the hemisphere. We describe an implementation on graphics hardware that performs real-time rendering of glossy objects with dynamic self-shadowing and interreflection without fixing the view or light as in previous work. Our approach also allows significantly increased lighting frequency when rendering diffuse objects and includes subsurface scattering.

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MP4 File (sloan_clustered.mp4)

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Published In

cover image ACM Conferences
SIGGRAPH '03: ACM SIGGRAPH 2003 Papers
July 2003
683 pages
ISBN:1581137095
DOI:10.1145/1201775
Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 July 2003

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Author Tags

  1. graphics hardware
  2. illumination
  3. monte carlo techniques
  4. rendering
  5. shadow algorithms

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SIGGRAPH '03 Paper Acceptance Rate 81 of 424 submissions, 19%;
Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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  • (2022)Neural Precomputed Radiance TransferComputer Graphics Forum10.1111/cgf.1448041:2(365-378)Online publication date: 24-May-2022
  • (2022)GPU-Based Techniques for Global Illumination EffectsundefinedOnline publication date: 21-Mar-2022
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  • (2017)Interactive directional subsurface scattering and transport of emergent lightThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-016-1207-233:3(371-383)Online publication date: 1-Mar-2017
  • (2012)BibliographyShadow Algorithms Data Miner10.1201/b11901-9(197-238)Online publication date: 23-Aug-2012
  • (2012)The State of the Art in Interactive Global IlluminationComputer Graphics Forum10.1111/j.1467-8659.2012.02093.x31:1(160-188)Online publication date: 1-Feb-2012
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  • (2011)SSLPVProceedings of the ACM SIGGRAPH Symposium on High Performance Graphics10.1145/2018323.2018325(7-14)Online publication date: 5-Aug-2011
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