Geometric Sample Reweighting for Monte Carlo Integration

J. Guo, E. Eisemann*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
34 Downloads (Pure)

Abstract

Numerical integration is fundamental in multiple Monte Carlo rendering problems. We present a sample reweighting scheme, including underlying theory, and analysis of numerical performance for the integration of an unknown one-dimensional function. Our method is simple to implement and builds upon the insight to link the weights to a function reconstruction process during integration. We provide proof that our solution is unbiased in one-dimensional cases and consistent in multi-dimensional cases. We illustrate its effectiveness in several use cases.

Original languageEnglish
Pages (from-to)109-119
Number of pages11
JournalComputer Graphics Forum
Volume40
Issue number7
DOIs
Publication statusPublished - 2021

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • CCS Concepts
  • Monte Carlo Integration
  • Rendering
  • Sample Reweighting
  • Sampling and Reconstruction
  • • Computing methodologies → Ray tracing

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