Globally Adaptive Control Variate for Robust Numerical Integration
Many methods in computer graphics require the integration of functions on low-to-middle--dimensional spaces. However, no available method can handle all the possible integrands accurately and rapidly. This paper presents a robust numerical integration method, able to handle arbitrary nonsingular sca...
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Published in | SIAM journal on scientific computing Vol. 36; no. 4; pp. A1708 - A1730 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Society for Industrial and Applied Mathematics
01.01.2014
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Subjects | |
Online Access | Get full text |
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Summary: | Many methods in computer graphics require the integration of functions on low-to-middle--dimensional spaces. However, no available method can handle all the possible integrands accurately and rapidly. This paper presents a robust numerical integration method, able to handle arbitrary nonsingular scalar or vector-valued functions defined on low-to-middle--dimensional spaces. Our method combines control variate, globally adaptive subdivision and Monte-Carlo estimation to achieve fast and accurate computations of any nonsingular integral. The runtime is linear with respect to standard deviation while standard Monte-Carlo methods are quadratic. We additionally show through numerical tests that our method is extremely stable from a computation time and memory footprint point of view, assessing its robustness. We demonstrate our method on a participating media voxelization application, which requires the computation of several millions integrals for complex media. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 1064-8275 1095-7197 |
DOI: | 10.1137/130937846 |