Fast Procedural Noise By Monte Carlo Sampling
dc.contributor.author | Fajardo, Marcos | en_US |
dc.contributor.author | Pharr, Matt | en_US |
dc.contributor.editor | Ritschel, Tobias | en_US |
dc.contributor.editor | Weidlich, Andrea | en_US |
dc.date.accessioned | 2023-06-27T06:42:00Z | |
dc.date.available | 2023-06-27T06:42:00Z | |
dc.date.issued | 2023 | |
dc.description.abstract | Procedural noise functions are widely used in computer graphics as a way to add texture detail to surfaces and volumes. Many noise functions are based on weighted sums that can be expressed in terms of random variables, which makes it possible to compute Monte Carlo estimates of their values at lower cost. Such stochastic noise functions fit naturally into many Monte Carlo estimators already used in rendering. Leveraging the dense image-plane sampling in modern path tracing renderers, we show that stochastic evaluation allows the use of procedural noise at a fraction of its full cost with little additional error. | en_US |
dc.description.sectionheaders | Industry Track | |
dc.description.seriesinformation | Eurographics Symposium on Rendering | |
dc.identifier.doi | 10.2312/sr.20231141 | |
dc.identifier.isbn | 978-3-03868-228-8 | |
dc.identifier.issn | 1727-3463 | |
dc.identifier.pages | 131-137 | |
dc.identifier.pages | 7 pages | |
dc.identifier.uri | https://doi.org/10.2312/sr.20231141 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/sr20231141 | |
dc.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject | CCS Concepts: Computing methodologies -> Rendering; Texturing | |
dc.subject | Computing methodologies | |
dc.subject | Rendering | |
dc.subject | Texturing | |
dc.title | Fast Procedural Noise By Monte Carlo Sampling | en_US |