Data-driven BRDF models using real material measurements have become increasingly prevalent due to the development of novel gonioreflectometers, but efficient use of these models in many graphical applications remains challenging due to the few functionalities the raw data could provide. To ameliorate this issue, we propose to analyze BRDFs using directional statistics for better handling and exploring measured materials, especially isotropic materials, with efficient computation and compact storage. We conduct a thorough statistical analysis on both analytical BRDF models and measured materials from the MERL database. We show that different aspects of visual appearance can be characterized by different spherical moments, from which several descriptive measures can be derived to further facilitate their usage. We demonstrate how these measures are best leveraged in some graphical applications including gamut mapping using a new BRDF similarity measure, BRDF or SVBRDF reconstruction based on material clustering, and importance sampling for measured materials based on fast extracted GGX distributions. We finally show the potential of our approach in the categorization of surface reflectance types which is common for traditional photon mapping.

In this paper, we present an efficient framework for editing the appearance of measured materials. First, we separate the material data into diffuse and specular parts, which is important for measured BRDFs since editing without distinguishing the two parts makes the results less predictive. Additionally, the albedo of each part is calculated for later color editing. Next, we use a novel method to cluster the materials by their gloss levels and select the representative material of every level. With this at hand, the roughness, i.e., shape of the specular highlights can be adjusted among different levels. Finally, we reconstruct the edited materials which can be directly used in both online and offline rendering. We test the framework on the MERL dataset to validate the effectiveness of our method.

In this paper, we propose a depth restoration method using a novel superpixel technique. Guided by a normal map reconstructed from the raw depth data, this technique over-segments RGB-D images into many small regions where their depth is assumed to be smooth. As the raw depth data is incomplete, we further introduce a depth confidence map to identify the regions which are more reliable. With the produced superpixels, we can restore the incomplete depth map using a per-superpixel linear regression. A multiresolution superpixel strategy is employed when some superpixels do not contain enough valid data. Experiments show that the proposed depth restoration method can effectively fill the wide gaps along depth discontinuities without blurring the object boundaries and the depth discontinuities.

Abstract An appearance model for materials adhered with massive collections of special effect pigments has to take both high‐frequency spatial details (e.g., glints) and wave‐optical effects (e.g., iridescence) due to thin‐film interference into account. However, either phenomenon is challenging to characterize and simulate in a physically accurate way. Capturing these fascinating effects in a unified framework is even harder as the normal distribution function and the reflectance term are highly correlated and cannot be treated separately. In this paper, we propose a multi‐scale BRDF model for reproducing the main visual effects generated by the discrete assembly of special effect pigments, enabling a smooth transition from fine‐scale surface details to large‐scale iridescent patterns. We demonstrate that the wavelength‐dependent reflectance inside the pixel's footprint follows a Gaussian distribution according to the central limit theorem, and is closely related to the distribution of the thin‐film's thickness. We efficiently determine the mean and the variance of this Gaussian distribution for each pixel whose closed‐form expressions can be derived by assuming that the thin‐film's thickness is uniformly distributed. To validate its effectiveness, the proposed model is compared against some previous methods and photographs of actual materials. Furthermore, since our method does not require any scene‐dependent precomputation, the distribution of thickness is allowed to be spatially‐varying.

We introduce an analytical BRDF model tailored to the realistic rendering of retroreflective materials. Though these specially-designed materials are frequently encountered in our daily life, such as high-visibility clothing and traffic signs, their reflectance behaviors are barely analyzed and simulated in a physically meaningful manner in computer graphics. To understand how retroreflection is actually generate, we conduct a detailed optical analysis on a typical prismatic sheet which is the most widely used retroreflector in the material industry. In particular, the effective retroreflective area of the sheet is studied theoretically and experimentally. Based on the study, we derive a practical BRDF model that takes into account all types of reflection from the sheet, including mirror reflection, retroreflection, and diffuse reflection. Experiments confirm that our BRDF can produce visually pleasing rendered images with high fidelity retroreflection effects which closely match those generated by the prismatic sheet.

Realistic Rendering of thin transparent layers bounded by rough surfaces involves substantial expense of computation time to account for multiple internal reflections. Resorting to Monte Carlo rendering for such material is usually impractical since recursive importance sampling is inevitable. To reduce the burden of sampling for simulating subsurface scattering and hence improve rendering performance, we adapt the microfacet model to the material with a single thin layer by introducing the extended normal distribution function (ENDF), a new representation of this model, to express visually perceived roughness due to multiple bounces of reflections and refractions. With such a representation, both surface reflection and subsurface scattering can be treated in the same microfacet framework, and the sampling process can be reduced to only once for each bounce of scattering. We derive analytical expressions of the ENDF for several cases using joint spherical warping. We also show how to choose proper shadowing-masking and Fresnel terms to make the proposed bidirectional scattering distribution function (BSDF) model energy-conserving. Experiments demonstrate that our model can be easily incorporated into a Monte Carlo path tracer with little extra computational and storage overhead, enabling some real-time applications.

Web service recommendation plays an important role in building reliable service-oriented systems for both the service providers and the active users. However, with the proliferation of web services on the World Wide Web, traditional service recommendation is hard to accurately provide customized services to active users. In this paper, we propose a novel web service recommender model using collaborative filtering to improve the prediction of Quality-of-Services. Benefiting from the accuracy of hybrid recommenders, we extend the idea of optimized predicting order and design the Graph to describe the neighborhood. Furthermore, a new algorithm using adjusted topological sorting for Graph is proposed to generate the optimized order while predicting. Finally, we conduct extensive experiments to evaluate our proposed model, in which a real data set with 1.5 million invocation information is taken as input. The experiment results show that our model achieves higher prediction accuracy than other models.

We present a novel approach for real-time rendering of transparent objects with multi-scale rough refraction under all-frequency environmental lighting. In our rendering system, the normal distribution function (NDF) of the surface bumps is expressed via mixtures of von Mises-Fisher (vMF) distributions, while the corresponding perturbation of refracted rays (RDF) can be approximated as a spherical warp of NDF, taking into account correction factors. Under the assumption of two-sided refraction, we first generate the vMF lobes of the front surface refraction. Based on these lobes, we then estimate the RDF of back surface as a warped convolution of macroscopic and microscopic NDFs within the footprint of each lobe. Moreover, summed-area tables and dual-paraboloid maps are adopted to efficiently represent the environmental lighting in order to support fully dynamic lighting conditions. We finally get a coherent rendering at the different scales that reproduces high-quality meso- and micro-geometric effects under real-time performance.

Line segment sampling has recently been adopted in many rendering algorithms for better handling of a wide range of effects such as motion blur, defocus blur and scattering media. A question naturally raised is how to generate line segment samples with good properties that can effectively reduce variance and aliasing artifacts observed in the rendering results. This paper studies this problem and presents a frequency analysis of line segment sampling. The analysis shows that the frequency content of a line segment sample is equivalent to the weighted frequency content of a point sample. The weight introduces anisotropy that smoothly changes among point samples, line segment samples and line samples according to the lengths of the samples. Line segment sampling thus makes it possible to achieve a balance between noise (point sampling) and aliasing (line sampling) under the same sampling rate. Based on the analysis, we propose a line segment sampling scheme to preserve blue-noise properties of samples which can significantly reduce noise and aliasing artifacts in reconstruction results. We demonstrate that our sampling scheme improves the quality of depth-of-field rendering, motion blur rendering, and temporal light field reconstruction.

Complex natural lighting provides better realism compared to traditional artificial lights, which has been increasing in real-time graphic applications, such as video games and virtual reality. However, rendering with complex natural illumination proves quite costly owing to a spherical space integral. This paper addresses the problem of real-time rendering scenes under complex environment lighting that captures soft shadows and glossy reflections. The environment lighting is separated into low-frequency lighting component and highlight component based on a rejection-based sampling method. Scenes lit under low-frequency lighting are approximated via spherical harmonic lighting, while highlight illumination effects such as soft shadows and glossy reflections are simulated by a small set of sampled virtual point lights (VPL). Experimental results demonstrate that our method can be run in real-time under complex natural lighting without precomputation.