Ling-Qi Yan

Rendering glints on high-resolution normal-mapped specular surfaces

Complex specular surfaces under sharp point lighting show a fascinating glinty appearance, but rendering it is an unsolved problem. Using Monte Carlo pixel sampling for this purpose is impractical: the energy is concentrated in tiny highlights that take up a minuscule fraction of the pixel. We instead compute an accurate solution using a completely different deterministic approach. Our method considers the true distribution of normals on a surface patch seen through a single pixel, which can be highly complex. We show how to evaluate this distribution efficiently, assuming a Gaussian pixel footprint and Gaussian intrinsic roughness. We also take advantage of hierarchical pruning of position-normal space to rapidly find texels that might contribute to a given normal distribution evaluation. Our results show complex, temporally varying glints from materials such as bumpy plastics, brushed and scratched metals, metallic paint and ocean waves.

Discrete stochastic microfacet models

This paper investigates rendering glittery surfaces, ones which exhibit shifting random patterns of glints as the surface or viewer moves. It applies both to dramatically glittery surfaces that contain mirror-like flakes and also to rough surfaces that exhibit more subtle small scale glitter, without which most glossy surfaces appear too smooth in close-up. These phenomena can in principle be simulated by high-resolution normal maps, but maps with tiny features create severe aliasing problems under narrow-angle illumination. In this paper we present a stochastic model for the effects of random subpixel structures that generates glitter and spatial noise that behave correctly under different illumination conditions and viewing distances, while also being temporally coherent so that they look right in motion. The model is based on microfacet theory, but it replaces the usual continuous microfacet distribution with a discrete distribution of scattering particles on the surface. A novel stochastic hierarchy allows efficient evaluation in the presence of large numbers of random particles, without ever having to consider the particles individually. This leads to a multiscale procedural BRDF that is readily implemented in standard rendering systems, and which converges back to the smooth case in the limit.

Physically-accurate fur reflectance: modeling, measurement and rendering

Rendering photo-realistic animal fur is a long-standing problem in computer graphics. Considerable effort has been made on modeling the geometric complexity of fur, but the reflectance of fur fibers is not well understood. Fur has a distinct diffusive and saturated appearance, that is not captured by either the Marschner hair model or the Kajiya-Kay model. In this paper, we develop a physically-accurate reflectance model for fur fibers. Based on anatomical literature and measurements, we develop a double cylinder model for the reflectance of a single fur fiber, where an outer cylinder represents the biological observation of a cortex covered by multiple cuticle layers, and an inner cylinder represents the scattering interior structure known as the medulla. Our key contribution is to model medulla scattering accurately---in contrast, for human hair, the medulla has minimal width and thus negligible contributions to the reflectance. Medulla scattering introduces additional reflection and transmission paths, as well as diffusive reflectance lobes. We validate our physical model with measurements on real fur fibers, and introduce the first database in computer graphics of reflectance profiles for nine fur samples. We show that our model achieves significantly better fits to the measured data than the Marschner hair reflectance model. For efficient rendering, we develop a method to precompute 2D medulla scattering profiles and analytically approximate our reflectance model with factored lobes. The accuracy of the approach is validated by comparing our rendering model to full 3D light transport simulations. Our model provides an enriched set of controls, where the parameters we fit can be directly used to render realistic fur, or serve as a starting point from which artists can manually tune parameters for desired appearances.

Fast 4D Sheared Filtering for Interactive Rendering of Distribution Effects

Soft shadows, depth of field, and diffuse global illumination are common distribution effects, usually rendered by Monte Carlo ray tracing. Physically correct, noise-free images can require hundreds or thousands of ray samples per pixel, and take a long time to compute. Recent approaches have exploited sparse sampling and filtering; the filtering is either fast (axis-aligned), but requires more input samples, or needs fewer input samples but is very slow (sheared). We present a new approach for fast sheared filtering on the GPU. Our algorithm factors the 4D sheared filter into four 1D filters. We derive complexity bounds for our method, showing that the per-pixel complexity is reduced from O(n2 l2) to O(nl), where n is the linear filter width (filter size is O(n2)) and l is the (usually very small) number of samples for each dimension of the light or lens per pixel (spp is l2). We thus reduce sheared filtering overhead dramatically. We demonstrate rendering of depth of field, soft shadows and diffuse global illumination at interactive speeds. We reduce the number of samples needed by 5-8×, compared to axis-aligned filtering, and framerates are 4× faster for equal quality.

Accurate Translucent Material Rendering under Spherical Gaussian Lights

In this paper we present a new algorithm for accurate rendering of translucent materials under Spherical Gaussian (SG) lights. Our algorithm builds upon the quantized‐diffusion BSSRDF model recently introduced in [ dI11 ]. Our main contribution is an efficient algorithm for computing the integral of the BSSRDF with an SG light. We incorporate both single and multiple scattering components. Our model improves upon previous work by accounting for the incident angle of each individual SG light. This leads to more accurate rendering results, notably elliptical profiles from oblique illumination. In contrast, most existing models only consider the total irradiance received from all lights, hence can only generate circular profiles. Experimental results show that our method is suitable for rendering of translucent materials under finite‐area lights or environment lights that can be approximated by a small number of SGs.

Position-normal distributions for efficient rendering of specular microstructure

Specular BRDF rendering traditionally approximates surface microstructure using a smooth normal distribution, but this ignores glinty effects, easily observable in the real world. While modeling the actual surface microstructure is possible, the resulting rendering problem is prohibitively expensive. Recently, Yan et al. [2014] and Jakob et al. [2014] made progress on this problem, but their approaches are still expensive and lack full generality in their material and illumination support. We introduce an efficient and general method that can be easily integrated in a standard rendering system. We treat a specular surface as a four-dimensional position-normal distribution, and fit this distribution using millions of 4D Gaussians, which we call elements. This leads to closed-form solutions to the required BRDF evaluation and sampling queries, enabling the first practical solution to rendering specular microstructure.

An efficient and practical near and far field fur reflectance model

Physically-based fur rendering is difficult. Recently, structural differences between hair and fur fibers have been revealed by Yan et al. (2015), who showed that fur fibers have an inner scattering medulla, and developed a double cylinder model. However, fur rendering is still complicated due to the complex scattering paths through the medulla. We develop a number of optimizations that improve efficiency and generality without compromising accuracy, leading to a practical fur reflectance model. We also propose a key contribution to support both near and far-field rendering, and allow smooth transitions between them. Specifically, we derive a compact BCSDF model for fur reflectance with only 5 lobes. Our model unifies hair and fur rendering, making it easy to implement within standard hair rendering software, since we keep the traditional R, TT, and TRT lobes in hair, and only add two extensions to scattered lobes, TTs and TRTs. Moreover, we introduce a compression scheme using tensor decomposition to dramatically reduce the precomputed data storage for scattered lobes to only 150 KB, with minimal loss of accuracy. By exploiting piecewise analytic integration, our method further enables a multi-scale rendering scheme that transitions between near and far field rendering smoothly and efficiently for the first time, leading to 6 -- 8× speed up over previous work.

Rendering Specular Microgeometry with Wave Optics

Simulation of light reflection from specular surfaces is a core problem of computer graphics. Existing solutions either make the approximation of providing only a large-area average solution in terms of a fixed BRDF (ignoring spatial detail), or are specialized for specific microgeometry (e.g. 1D scratches), or are based only on geometric optics (which is an approximation to more accurate wave optics). We design the first rendering algorithm based on a wave optics model that is also able to compute spatially-varying specular highlights with high-resolution detail on general surface microgeometry. We compute a wave optics reflection integral over the coherence area; our solution is based on approximating the phase-delay grating representation of a micron-resolution surface heightfield using Gabor kernels. We found that the appearance difference between the geometric and wave solution is more dramatic when spatial detail is taken into account. The visualizations of the corresponding BRDF lobes differ significantly. Moreover, the wave optics solution varies as a function of wavelength, predicting noticeable color effects in the highlights. Our results show both single-wavelength and spectral solution to reflection from common everyday objects, such as brushed, scratched and bumpy metals.

Multiple Axis-Aligned Filters for Rendering of Combined Distribution Effects

Distribution effects such as diffuse global illumination, soft shadows and depth of field, are most accurately rendered using Monte Carlo ray or path tracing. However, physically accurate algorithms can take hours to converge to a noise‐free image. A recent body of work has begun to bridge this gap, showing that both individual and multiple effects can be achieved accurately and efficiently. These methods use sparse sampling, GPU raytracers, and adaptive filtering for reconstruction. They are based on a Fourier analysis, which models distribution effects as a wedge in the frequency domain. The wedge can be approximated as a single large axis‐aligned filter, which is fast but retains a large area outside the wedge, and therefore requires a higher sampling rate; or a tighter sheared filter, which is slow to compute. The state‐of‐the‐art fast sheared filtering method combines low sampling rate and efficient filtering, but has been demonstrated for individual distribution effects only, and is limited by high‐dimensional data storage and processing.