Gaussian Product Sampling for Rendering Layered Materials
Gaussian Product Sampling for Rendering Layered Materials
复制标题
用于渲染分层材质的高斯积采样
DOI：
10.1111/cgf.13883
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发表时间：
2019
影响因子：
2.5
通讯作者：
Marschner, Steve
中科院分区：
文献类型：
--
作者：
Xia, Mengqi;Walter, Bruce;Hery, Christophe;Marschner, Steve
为了增加多样性和真实性，表面双向散射分布函数（BSDF）通常被建模为由多个层组成，但准确评估分层BSDF，同时考虑所有光传输路径是一个具有挑战性的问题。最近，Guoet al. [GHZ 18]提出了一种准确和通用的无位置蒙特卡罗方法，但与非随机分层模型相比，该方法引入了导致渲染时间更长的方差。本文改进了以往的工作，提出了两种新的抽样策略：对产品抽样和多产品抽样.我们的新方法更好地利用分层结构，减少方差相比，传统的方法顺序采样一个BSDF的时间。Ourpair-product samplingstrategy importance从一对相邻层中抽取两个BSDF的乘积。我们进一步将其推广到多积采样，即对三个或更多BSDF链的乘积进行重要性采样。为了计算这些乘积，我们开发了一种新的单层BSDF的近似高斯表示。这种表示法将空间变化的材料特性作为参数，使我们的技术可以支持任意数量的纹理层。与以前的蒙特卡罗分层方法相比，我们的研究结果表明，显着的方差减少渲染各向同性分层表面。
To increase diversity and realism, surface bidirectional scattering distribution functions (BSDFs) are often modelled as consisting of multiple layers, but accurately evaluating layered BSDFs while accounting for all light transport paths is a challenging problem. Recently, Guoet al. [GHZ18] proposed an accurate and general position‐free Monte Carlo method, but this method introduces variance that leads to longer render time compared to non‐stochastic layered models. We improve the previous work by presenting two new sampling strategies,pair‐product samplingandmultiple‐product sampling. Our new methods better take advantage of the layered structure and reduce variance compared to the conventional approach of sequentially sampling one BSDF at a time. Ourpair‐product samplingstrategy importance samples the product of two BSDFs from a pair of adjacent layers. We further generalize this tomultiple‐product sampling, which importance samples the product of a chain of three or more BSDFs. In order to compute these products, we developed a new approximate Gaussian representation of individual layer BSDFs. This representation incorporates spatially varying material properties as parameters so that our techniques can support an arbitrary number of textured layers. Compared to previous Monte Carlo layering approaches, our results demonstrate substantial variance reduction in rendering isotropic layered surfaces.
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DOI：
10.1145/3272127.3275053
发表时间：
2018-12
期刊：
ACM Transactions on Graphics (TOG)
影响因子：
--
作者：
Yu Guo;Miloš Hašan;Shuang Zhao
通讯作者：
Yu Guo;Miloš Hašan;Shuang Zhao
DOI：
10.1145/2601097.2601203
发表时间：
2014-07
期刊：
ACM Transactions on Graphics (TOG)
影响因子：
--
作者：
J. Vorba;Ondrej Karlik;M. Šik;Tobias Ritschel;Jaroslav Křivánek
通讯作者：
J. Vorba;Ondrej Karlik;M. Šik;Tobias Ritschel;Jaroslav Křivánek
DOI：
10.1145/3197517.3201351
发表时间：
2018-07
期刊：
ACM Transactions on Graphics (TOG)
影响因子：
--
作者：
Ling-Qi Yan;Miloš Hašan;B. Walter;Steve Marschner;R. Ramamoorthi
通讯作者：
Ling-Qi Yan;Miloš Hašan;B. Walter;Steve Marschner;R. Ramamoorthi
基于参数混合模型的高效 BRDF 采样统一流形框架
DOI：
10.2312/sre.20181171
发表时间：
2018
期刊：
ACM Transactions on Graphics (TOG)
影响因子：
--
作者：
Sebastian Herholz;Oskar Elek;Jens Schindel;Jaroslav Křivánek;H. Lensch
通讯作者：
H. Lensch