Road marking BRDF model applicable for a wide range of incident illumination conditions

To drive safely and comfortably, an adequate contrast between the road surface and road markings is needed. This contrast can be improved by using optimized road illumination designs and luminaires with dedicated luminous intensity distributions, taking advantage of the (retro)reflective characteristics of the road surface and road markings. Since little is known about road markings’ (retro)reflective characteristics for the incident and viewing angles relevant for street luminaires, bidirectional reflectance distribution function (BRDF)-values of some retroreflective materials are measured for a wide range of illumination and viewing angles using a luminance camera in a commercial near-field goniophotometer setup. The experimental data are fitted to a new and optimized “RetroPhong” model, which shows good agreement with the data [root mean squared error (RMSE) &lt; 0.13, normalized root mean squared error (NRMSE) &lt; 0.04, and the normalized cross correlation ratio (NCC) &gt; 0.8]. The RetroPhong model is benchmarked with other relevant (retro)reflective BRDF models, and the results suggest that the RetroPhong model is most suitable for the current set of samples and measurement conditions.</p

Dynamic Display of BRDFs

This paper deals with the challenge of physically displaying reflectance, i.e., the appearance of a surface and its variation with the observer position and the illuminating environment. This is commonly described by the bidirectional reflectance distribution function (BRDF). We provide a catalogue of criteria for the display of BRDFs, and sketch a few orthogonal approaches to solving the problem in an optically passive way. Our specific implementation is based on a liquid surface, on which we excite waves in order to achieve a varying degree of anisotropic roughness. The resulting probability density function of the surface normal is shown to follow a Gaussian distribution similar to most established BRDF models

An Overview of BRDF Models

This paper is focused on the Bidirectional Reflectance Distribution Function (BRDF) in the context of algorithms for computational production of realistic synthetic images. We provide a review of most relevant analytical BRDF models proposed in the literature which have been used for realistic rendering. We also show different approaches used for obtaining efficient models from acquired reflectance data, and the related function fitting techniques, suitable for using that data in efficient rendering algorithms. We consider algorithms for computation of BRDF integrals, by using Monte-Carlo based numerical integration. In this context, we review known techniques to design efficient BRDF sampling schemes for both analytical and measured BRDF models.The authors have been partially supported by the Spanish Research Program under project TIN2004-07672-C03-02 and the Andalusian Research Program under project P08-TIC-03717

Comprehensive polarimetric analysis of Spectralon white reflectance standard in a wide visible range

Since polarimetry has extended its use for the study of scattering from surfaces and tissues, Spectralon, a white reflectance standard, is acquiring the role of a polarimetric standard. Both the behavior of Spectralon as a Lambertian surface and its performance as a perfect depolarizer are analyzed in detail. The accuracy of our dynamic polarimeter, together with the polar decomposition to describe the Mueller matrix (MM) depolarizing action, combine to produce a powerful tool for the proper analysis of this scattering surface. Results allowed us to revisit, for confirmation or revision, the role of some MM elements, as described in the bibliography. The conditions under which it can be considered a good Lambertian surface are specified in terms of incidence and scattering angle and verified over a large wavelength range

Perceptual Modeling and Reproduction of Gloss

The reproduction of gloss on displays is generally not based on perception and as a consequence does not guarantee the best visualization of a real material. The reproduction is composed of four different steps: measurement, modeling, rendering, and display. The minimum number of measurements required to approximate a real material is unknown. The error metrics used to approximate measurements with analytical BRDF models are not based on perception, and the best visual approximation is not always obtained. Finally, the gloss perception difference between real objects and objects seen on displays has not sufficiently been studied and might be influencing the observer judgement. This thesis proposes a systematic, scalable, and perceptually based workflow to represent real materials on displays. First, the gloss perception difference between real objects and objects seen on displays was studied. Second, the perceptual performance of the error metrics currently in use was evaluated. Third, a projection into a perceptual gloss space was defined, enabling the computation of a perceptual gloss distance measure. Fourth, the uniformity of the gloss space was improved by defining a new gloss difference equation. Finally, a systematic, scalable, and perceptually based workflow was defined using cost-effective instruments

BxDF material acquisition, representation, and rendering for VR and design

Photorealistic and physically-based rendering of real-world environments with high fidelity materials is important to a range of applications, including special effects, architectural modelling, cultural heritage, computer games, automotive design, and virtual reality (VR). Our perception of the world depends on lighting and surface material characteristics, which determine how the light is reflected, scattered, and absorbed. In order to reproduce appearance, we must therefore understand all the ways objects interact with light, and the acquisition and representation of materials has thus been an important part of computer graphics from early days. Nevertheless, no material model nor acquisition setup is without limitations in terms of the variety of materials represented, and different approaches vary widely in terms of compatibility and ease of use. In this course, we describe the state of the art in material appearance acquisition and modelling, ranging from mathematical BSDFs to data-driven capture and representation of anisotropic materials, and volumetric/thread models for patterned fabrics. We further address the problem of material appearance constancy across different rendering platforms. We present two case studies in architectural and interior design. The first study demonstrates Yulio, a new platform for the creation, delivery, and visualization of acquired material models and reverse engineered cloth models in immersive VR experiences. The second study shows an end-to-end process of capture and data-driven BSDF representation using the physically-based Radiance system for lighting simulation and rendering

Physically Based Lighting Models for Real Time Graphics Engines

Το αντικείμενο της πτυχιακής εργασίας αφορά τα ρεαλιστικά μοντέλα φωτισμού σε μηχανές γραφικών πραγματικού χρόνου. Τις τελευταίες δεκαετίες έχει γίνει σημαντική πρόοδος στα μοντέλα φωτισμού, ωστόσο το πρόβλημα της εξισορρόπησης μεταξύ του καλύτερου οπτικού αποτελέσματος και της καλύτερης επίδοσης παραμένει και ποικίλει ανάλογα το τελικό υλικό υπολογιστή που θα κληθεί να σχεδιαγραφήσει τα γραφικά.The subject of this thesis pertains to the physically based lighting models for real time game engines. Over the last decades, we have seen a great improvement in the lighting models, however, the dilemma between a good visual result and better performance still exists and has many variations depending on the hardware that will render the graphics

Acquisition and modeling of material appearance

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 131-143).In computer graphics, the realistic rendering of synthetic scenes requires a precise description of surface geometry, lighting, and material appearance. While 3D geometry scanning and modeling have advanced significantly in recent years, measurement and modeling of accurate material appearance have remained critical challenges. Analytical models are the main tools to describe material appearance in most current applications. They provide compact and smooth approximations to real materials but lack the expressiveness to represent complex materials. Data-driven approaches based on exhaustive measurements are fully general but the measurement process is difficult and the storage requirement is very high. In this thesis, we propose the use of hybrid representations that are more compact and easier to acquire than exhaustive measurement, while preserving much generality of a data-driven approach. To represent complex bidirectional reflectance distribution functions (BRDFs), we present a new method to estimate a general microfacet distribution from measured data. We show that this representation is able to reproduce complex materials that are impossible to model with purely analytical models.(cont.) We also propose a new method that significantly reduces measurement cost and time of the bidirectional texture function (BTF) through a statistical characterization of texture appearance. Our reconstruction method combines naturally aligned images and alignment-insensitive statistics to produce visually plausible results. We demonstrate our acquisition system which is able to capture intricate materials like fabrics in less than ten minutes with commodity equipments. In addition, we present a method to facilitate effective user design in the space of material appearance. We introduce a metric in the space of reflectance which corresponds roughly to perceptual measures. The main idea of our approach is to evaluate reflectance differences in terms of their induced rendered images, instead of the reflectance function itself defined in the angular domains. With rendered images, we show that even a simple computational metric can provide good perceptual spacing and enable intuitive navigation of the reflectance space.by Wai Kit Addy Ngan.Ph.D