Please use this identifier to cite or link to this item: doi:10.22028/D291-27753
Title: Efficient Caustic Rendering with Lightweight Photon Mapping
Author(s): Grittmann, Pascal
Pérard-Gayot, Arsène
Slusallek, Philipp
Křivánek, Jaroslav
Language: English
Title: Computer Graphics Forum
Volume: 37
Issue: 4
Pages: 133-142
Publisher/Platform: Wiley
Year of Publication: 2018
DDC notations: 500 Science
Publikation type: Journal Article
Abstract: Robust and efficient rendering of complex lighting effects, such as caustics, remains a challenging task. While algorithms like vertex connection and merging can render such effects robustly, their significant overhead over a simple path tracer is not always justified and – as we show in this paper ‐ also not necessary. In current rendering solutions, caustics often require the user to enable a specialized algorithm, usually a photon mapper, and hand‐tune its parameters. But even with carefully chosen parameters, photon mapping may still trace many photons that the path tracer could sample well enough, or, even worse, that are not visible at all. Our goal is robust, yet lightweight, caustics rendering. To that end, we propose a technique to identify and focus computation on the photon paths that offer significant variance reduction over samples from a path tracer. We apply this technique in a rendering solution combining path tracing and photon mapping. The photon emission is automatically guided towards regions where the photons are useful, i.e., provide substantial variance reduction for the currently rendered image. Our method achieves better photon densities with fewer light paths (and thus photons) than emission guiding approaches based on visual importance. In addition, we automatically determine an appropriate number of photons for a given scene, and the algorithm gracefully degenerates to pure path tracing for scenes that do not benefit from photon mapping.
DOI of the first publication: 10.1111/cgf.13481
Link to this record: urn:nbn:de:bsz:291--ds-277532
ISSN: 1467-8659
Date of registration: 26-Apr-2019
EU-Projectnumber: info:eu-repo/grantAgreement/EC/H2020/642841/EU//Distro
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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