Computer Graphics Forum Vol. 39 Issue 2 (Proceedings of Eurographics) 2020
An underwater scene which combines fluorescent surfaces and challenging
illumination. It features smooth dielectrics (the bottle) and
a rough conductor (the can) both with wavelength dependent IOR,
and a homogeneous chromatic medium. The light source is a large but focused
spot light, similar to caustic illumination under water, which is hard to
render with unidirectional methods.
The insets show a path tracer with next event estimation at equal time.
Right: the scene is illuminated exclusively by UV light,
left: visible and UV light. Both pictures are
rendered with our spectrally mollified bidirectional path tracer,
enabling bidirectional rendering in the presence of fluorescence.
Abstract
Fluorescent materials can shift energy between wavelengths, thereby creating bright and saturated colors both in natural and artificial materials.
However, rendering fluorescence for continuous wavelengths or combined with wavelength dependent path configurations so far has only been feasible using spectral unidirectional methods.
We present a regularization-based approach for supporting fluorescence in a spectral bidirectional path tracer.
Our algorithm samples camera and light sub-paths with independent wavelengths, and when connecting them mollifies the BSDF at one of the connecting vertices such that it reradiates light across multiple wavelengths.
We discuss arising issues such as color bias in early iterations, consistency of the method and MIS weights in the presence of spectral mollification.
We demonstrate our method in scenes combining fluorescence and transport phenomena that are difficult to render with unidirectional or spectrally discrete methods.
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Bibtex
@article {10.1111:cgf.13937,
journal = {Computer Graphics Forum},
title = {{Spectral Mollification for Bidirectional Fluorescence}},
author = {Jung, Alisa and Hanika, Johannes and Dachsbacher, Carsten},
year = {2020},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.13937}
}
