Geometric Sample Reweighting for Monte Carlo Integration

Journal article (2021)

Authors

J. Guo Computer Graphics and Visualisation
E. Eisemann Computer Graphics and Visualisation
Research Group
Computer Graphics and Visualisation
Copyright: © 2021 Jerry Jinfeng Guo, E. Eisemann
DOI: https://doi.org/10.1111/cgf.14405
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Published Date

2021

Language

English

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Research Group

Computer Graphics and Visualisation

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.

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