Position-free monte carlo simulation for arbitrary layered BSDFs
Position-free monte carlo simulation for arbitrary layered BSDFs
复制标题
DOI：
10.1145/3272127.3275053
复制
发表时间：
2018-12
期刊：
影响因子：
--
通讯作者：
Yu Guo;Miloš Hašan;Shuang Zhao
中科院分区：
文献类型：
--
作者：
Yu Guo;Miloš Hašan;Shuang Zhao
现实世界的材料通常是分层的：金属涂料，生物组织等等。层的界面和体积散射特性的变化导致材料外观的丰富多样性，从各向异性高光到复杂的纹理和浮雕图案。然而，模拟光层的相互作用是一个具有挑战性的问题。过去的分析或数值解决方案要么引入几个近似和限制，或依赖于离散化的BSDF上的昂贵的操作，防止在空间上自由地改变层属性的能力。本文提出了一种新的基于蒙特卡罗模拟的无偏分层BSDF模型，其唯一的假设是分层假设本身。我们的新的位置自由的路径配方是从根本上更强大的光传输路径比一般的光传输算法应用于平面层的特殊情况下，因为它是基于一个产品的立体角，而不是面积的措施，所以不包含高方差的几何条件需要在标准配方。我们介绍了两种技术采样的位置自由的路径积分，下一个事件估计和一个完整的双向估计的前向路径跟踪器。我们展示了一些例子，具有多个层的表面和体积散射，表面和相函数各向异性，以及所有参数的空间变化。
Real-world materials are often layered: metallic paints, biological tissues, and many more. Variation in the interface and volumetric scattering properties of the layers leads to a rich diversity of material appearances from anisotropic highlights to complex textures and relief patterns. However, simulating light-layer interactions is a challenging problem. Past analytical or numerical solutions either introduce several approximations and limitations, or rely on expensive operations on discretized BSDFs, preventing the ability to freely vary the layer properties spatially. We introduce a new unbiased layered BSDF model based on Monte Carlo simulation, whose only assumption is the layer assumption itself. Our novel position-free path formulation is fundamentally more powerful at constructing light transport paths than generic light transport algorithms applied to the special case of flat layers, since it is based on a product of solid angle instead of area measures, so does not contain the high-variance geometry terms needed in the standard formulation. We introduce two techniques for sampling the position-free path integral, a forward path tracer with next-event estimation and a full bidirectional estimator. We show a number of examples, featuring multiple layers with surface and volumetric scattering, surface and phase function anisotropy, and spatial variation in all parameters.