Real-time rendering of layered materials with anisotropic normal distributions

This paper proposes a lightweight bidirectional scattering distribution function(BSDF)model for layered materials with anisotropic reflection and refraction properties.In our method,each layer of the materials can be described by a microfacet BSDF using an anisotropic normal distribution function(NDF).Furthermore,the NDFs of layers can be defined on tangent vector fields,which differ from layer to layer.Our method is based on a previous study in which isotropic BSDFs are approximated by projecting them onto base planes.However,the adequateness of this previous work has not been well investigated for anisotropic BSDFs.In this paper,we demonstrate that the projection is also applicable to anisotropic BSDFs and that the BSDFs are approximated by elliptical distributions using covariance matrices.

Modified filtered importance sampling for virtual spherical Gaussian lights

This paper proposes a modification of the filtered importance sampling method, and improves the quality of virtual spherical Gaussian light(VSGL)-based real-time glossy indirect illumination using this modification. The original filtered importance sampling method produces large overlaps of and gaps between filtering kernels for high-frequency probability density functions(PDFs). This is because the size of the filtering kernel is determined using the PDF at the sampled center of the kernel. To reduce those overlaps and gaps, this paper determines the kernel size using the integral of the PDF within the filtering kernel. Our key insight is that these integrals are approximately constant, if kernel centers are sampled using stratified sampling. Therefore, an appropriate kernel size can be obtained by solving this integral equation. Using the proposed kernel size for filtered importance samplingbased VSGL generation, undesirable artifacts are significantly reduced with a negligibly small overhead.