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A Non-Parametric Factor Microfacet Model for Isotropic BRDFs

机译:各向同性BRDF的非参数因子微面模型

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We investigate the expressiveness of the microfacet model for isotropic bidirectional reflectance distribution functions (BRDFs) measured from real materials by introducing a non-parametric factor model that represents the model's functional structure but abandons restricted parametric formulations of its factors. We propose a new objective based on compressive weighting that controls rendering error in high-dynamic-range BRDF fits better than previous factorization approaches. We develop a simple numerical procedure to minimize this objective and handle dependencies that arise between microfacet factors. Our method faithfully captures a more comprehensive set of materials than previous state-of-the-art parametric approaches yet remains compact (3.2KB per BRDF). We experimentally validate the benefit of the microfacet model over a naive orthogonal factorization and show that fidelity for diffuse materials is modestly improved by fitting an unrestricted shadowing/masking factor. We also compare against a recent data-driven factorization approach [Bilgili et al. 2011] and show that our microfacet-based representation improves rendering accuracy for most materials while reducing storage by more than 10×.
机译:我们通过引入非参数因子模型(代表模型的功能结构,但放弃了其因子的受限参数公式),研究了从真实材料测量的各向同性双向反射分布函数(BRDF)的微面模型的表达。我们提出了一个基于压缩加权的新目标,该目标可控制高动态范围BRDF中的渲染误差,比以前的分解方法更适合。我们开发了一个简单的数值程序来最小化此目标并处理微面因素之间出现的依赖性。与以前的最新参数方法相比,我们的方法忠实地捕获了更全面的材料集,但仍保持紧凑(每个BRDF 3.2KB)。我们通过实验验证了微面模型相对于朴素的正交分解的好处,并表明通过拟合无限制的阴影/遮罩因子,适度提高了扩散材料的保真度。我们还与最近的数据驱动的因式分解方法进行了比较[Bilgili等。 2011],并表明我们基于微面的表示方法提高了大多数材质的渲染精度,同时将存储量减少了10倍以上。

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