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Temporal light field reconstruction for rendering distribution effects

Published: 25 July 2011 Publication History

Abstract

Traditionally, effects that require evaluating multidimensional integrals for each pixel, such as motion blur, depth of field, and soft shadows, suffer from noise due to the variance of the high-dimensional integrand. In this paper, we describe a general reconstruction technique that exploits the anisotropy in the temporal light field and permits efficient reuse of samples between pixels, multiplying the effective sampling rate by a large factor. We show that our technique can be applied in situations that are challenging or impossible for previous anisotropic reconstruction methods, and that it can yield good results with very sparse inputs. We demonstrate our method for simultaneous motion blur, depth of field, and soft shadows.

Supplementary Material

MP4 File (tp032_11.mp4)

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Cited By

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  • (2023)Computational Long Exposure Mobile PhotographyACM Transactions on Graphics10.1145/359212442:4(1-15)Online publication date: 26-Jul-2023
  • (2022)Spatiotemporal Variance-Guided Filtering for Motion BlurProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/35438715:3(1-13)Online publication date: 27-Jul-2022
  • (2021)Geometric Sample Reweighting for Monte Carlo IntegrationComputer Graphics Forum10.1111/cgf.1440540:7(109-119)Online publication date: 27-Nov-2021
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Information

Published In

cover image ACM Transactions on Graphics
ACM Transactions on Graphics  Volume 30, Issue 4
July 2011
829 pages
ISSN:0730-0301
EISSN:1557-7368
DOI:10.1145/2010324
Issue’s Table of Contents
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 July 2011
Published in TOG Volume 30, Issue 4

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Author Tags

  1. depth of field
  2. light field
  3. motion blur
  4. reconstruction
  5. soft shadows

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Cited By

View all
  • (2023)Computational Long Exposure Mobile PhotographyACM Transactions on Graphics10.1145/359212442:4(1-15)Online publication date: 26-Jul-2023
  • (2022)Spatiotemporal Variance-Guided Filtering for Motion BlurProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/35438715:3(1-13)Online publication date: 27-Jul-2022
  • (2021)Geometric Sample Reweighting for Monte Carlo IntegrationComputer Graphics Forum10.1111/cgf.1440540:7(109-119)Online publication date: 27-Nov-2021
  • (2020)Hybrid DoF: Ray-Traced and Post-Processed Hybrid Depth of Field Effect for Real-Time RenderingACM SIGGRAPH 2020 Posters10.1145/3388770.3407426(1-2)Online publication date: 17-Aug-2020
  • (2020)Adaptive Incident Radiance Field Sampling and Reconstruction Using Deep Reinforcement LearningACM Transactions on Graphics10.1145/336831339:1(1-17)Online publication date: 29-Jan-2020
  • (2020)Image Synthesis With Efficient Defocus Blur for Stereoscopic DisplaysIEEE Access10.1109/ACCESS.2020.30263328(176304-176312)Online publication date: 2020
  • (2020)Light-Field Raw Data Synthesis From RGB-D Images: Pushing to the ExtremeIEEE Access10.1109/ACCESS.2020.29740638(33391-33405)Online publication date: 2020
  • (2018)Laplacian kernel splatting for efficient depth-of-field and motion blur synthesis or reconstructionACM Transactions on Graphics10.1145/3197517.320137937:4(1-11)Online publication date: 30-Jul-2018
  • (2018)Denoising Deep Monte Carlo RenderingsComputer Graphics Forum10.1111/cgf.1353338:1(316-327)Online publication date: 27-Aug-2018
  • (2018)Removing Monte Carlo noise using a Sobel operator and a guided image filterThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-017-1363-z34:4(589-601)Online publication date: 1-Apr-2018
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