Hua, QingqinFichet, AlbanWilkie, AlexanderBousseau, Adrien and McGuire, Morgan2021-07-122021-07-122021978-3-03868-157-11727-3463https://doi.org/10.2312/sr.20211305https://diglib.eg.org:443/handle/10.2312/sr20211305We propose a technique to efficiently importance sample and store fluorescent spectral data. Fluorescence behaviour is properly represented as a re-radiation matrix: for a given input wavelength, this matrix indicates how much energy is re-emitted at all other wavelengths. However, such a 2D representation has a significant memory footprint, especially when a scene contains a high number of fluorescent objects, or fluorescent textures. We propose to use Gaussian Mixture Domain to model re-radiation, which allows us to significantly reduce the memory footprint. Instead of storing the full matrix, we work with a set of Gaussian parameters that also allow direct importance sampling. When accuracy is a concern, one can still use the re-radiation matrix data, and just benefit from importance sampling provided by the Gaussian Mixture. Our method is useful when numerous fluorescent materials are present in a scene, an in particular for textures with fluorescent components.Computing methodologiesReflectance modeling10.2312/sr.20211305225-234