Online Photon Guiding with 3D Gaussians for Caustics Rendering

Fuente: arXiv
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Autores principales: Huang, Jiawei, Tanaka, Hajime, Komura, Taku, Kitamura, Yoshifumi
Formato: Preprint
Publicado: 2024
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author Huang, Jiawei
Tanaka, Hajime
Komura, Taku
Kitamura, Yoshifumi
author_facet Huang, Jiawei
Tanaka, Hajime
Komura, Taku
Kitamura, Yoshifumi
contents In production rendering systems, caustics are typically rendered via photon mapping and gathering, a process often hindered by insufficient photon density. In this paper, we propose a novel photon guiding method to improve the photon density and overall quality for caustic rendering. The key insight of our approach is the application of a global 3D Gaussian mixture model, used in conjunction with an adaptive light sampler. This combination effectively guides photon emission in expansive 3D scenes with multiple light sources. By employing a global 3D Gaussian mixture, our method precisely models the distribution of the points of interest. To sample emission directions from the distribution at any observation point, we introduce a novel directional transform of the 3D Gaussian, which ensures accurate photon emission guiding. Furthermore, our method integrates a global light cluster tree, which models the contribution distribution of light sources to the image, facilitating effective light source selection. We conduct experiments demonstrating that our approach robustly outperforms existing photon guiding techniques across a variety of scenarios, significantly advancing the quality of caustic rendering.
format Preprint
id arxiv_https___arxiv_org_abs_2403_03641
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Online Photon Guiding with 3D Gaussians for Caustics Rendering
Huang, Jiawei
Tanaka, Hajime
Komura, Taku
Kitamura, Yoshifumi
Graphics
In production rendering systems, caustics are typically rendered via photon mapping and gathering, a process often hindered by insufficient photon density. In this paper, we propose a novel photon guiding method to improve the photon density and overall quality for caustic rendering. The key insight of our approach is the application of a global 3D Gaussian mixture model, used in conjunction with an adaptive light sampler. This combination effectively guides photon emission in expansive 3D scenes with multiple light sources. By employing a global 3D Gaussian mixture, our method precisely models the distribution of the points of interest. To sample emission directions from the distribution at any observation point, we introduce a novel directional transform of the 3D Gaussian, which ensures accurate photon emission guiding. Furthermore, our method integrates a global light cluster tree, which models the contribution distribution of light sources to the image, facilitating effective light source selection. We conduct experiments demonstrating that our approach robustly outperforms existing photon guiding techniques across a variety of scenarios, significantly advancing the quality of caustic rendering.
title Online Photon Guiding with 3D Gaussians for Caustics Rendering
topic Graphics
url https://arxiv.org/abs/2403.03641