Material Appearance Modeling

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Geometric Accuracy Analysis of Stationary BTF Gonioreflectometers
(The Eurographics Association, 2015) Havran, V.; Reinhard Klein and Holly Rushmeier
The accurate BTF data representation requires specialized measurement gantries, some of them designed as gonireflectometers. These consist of an illumination source and a camera mounted on two robotic arms, one degree of freedom possibly achieved by rotation stage which a measured sample is mounted on. While there are several variations of the gonioreflectometer gantry, the principle of all remains the same, positioning directly the illumination and detector on a hemispherical surface over a sample. We analyze the positioning error of such gonioreflectometers. The input parameters are the required spatial resolution of a BTF sample and the distance between the camera used as a detector and the BTF sample. Our analysis confirms that the requirements for mechatronic actuators for the positioning of the sample and arms are very high and near the limit of state of the art technology.
Grand Challenges: Material Models in the Automotive Industry
(The Eurographics Association, 2013) Schregle, R.; Denk, C.; Slusallek, P.; Glencross, M.; Reinhard Klein and Holly Rushmeier
Material reflectance definitions are core to high fidelity visual simulation of objects within a compelling 3D scene. In the automotive industry these are used across the entire business process: from conceptualisation of a new product range, through to the final sale. However, current state-of-the-art of material representations leave much to be desired for fast and practical deployment in the industry. Even after decades of research and development, there are no interoperable standards for material models to facilitate exchange between applications. A large discrepancy also exists between the quality of material models used (and indeed the quality at which they can be displayed) across the spectrum of use-cases within the industry. Focussing on the needs of the Automotive Industry, in this position paper, we summarise the main issues that limit the effective use of material models. Furthermore, we outline specific solutions we believe could be investigated in order to address this problem. This paper is the result of a review conducted in conjunction with several key players in the automotive field.
Linear Models for Material BTFs and Possible Applications
(The Eurographics Association, 2015) Brok, D. den; Weinmann, M.; Klein, R.; Reinhard Klein and Holly Rushmeier
Due to the richness of real-world materials, arguably one of the biggest challenges in rendering is to come up with models that describe their appearance well. The image-based bidirectional texture function (BTF) is known to be able to model many effects that are hard or impossible to reproduce with analytical reflectance models. This advantage comes at the price of demanding storage and acquisition requirements. In previous work, we have demonstrated that these requirements can be lifted to some extent by means of data-driven linear models. We give a more in-depth overview on our research on such models and summarize the applications we investigated so far, followed by an outlook on what might yet be achievable.
On the Advancement of BTF Measurement on Site
(The Eurographics Association, 2018) Havran, Vlastimil; Hosek, Jan; Nemcova, Sarka; Cap, Jiri; Reinhard Klein and Holly Rushmeier
We present our progress to the on-site measurement of the spatially varying surface reflectance represented by bidirectional texture function (BTF). This requires a physical realization of a portable instrument that can be brought to the sample, outside the laboratory. We discuss our motivation, the main issues, and challenges for making such an instrument possible. We focus on the design of the mechanical parts that are required for an easy manipulation of the device on site and describe our experiences with the instrument in practice. The design uses a miniaturized rotary light stage. It allows for measurement of HDR images with the acquisition rate of 1000 HDR images per minute, where one HDR image consists of 4 individual exposures.
Practical Experiences with Using Autocollimator for Surface Reflectance Measurement
(The Eurographics Association, 2016) Havran, Vlastimil; Reinhard Klein and Holly Rushmeier
We present our experiences with using an autocollimator to set up the surface reflectance measurement for both BRDF and BTF. Assuming the measured material appearance is put on a locally flat surface, the autocollimator allows us to set the perpendicularity of the measured sample in stationary measurement setups. The principle works also vice versa, we can align the measurement setup against a stationary sample for on-site measurements. The autocollimator requires to use a collimated beam of light, a mirror, a beam splitter, and a detector. We describe the autocollimator principle, problems, and the issues involved when using an autocollimator for surface reflectance measurement setups.
The Problem of Entangled Material Properties in SVBRDF Recovery
(The Eurographics Association, 2020) Saryazdi, Soroush; Murphy, Christian; Mudur, Sudhir; Klein, Reinhard and Rushmeier, Holly
SVBRDF (spatially varying bidirectional reflectance distribution function) recovery is concerned with deriving the material properties of an object from one or more images. This problem is particularly challenging when the images are casual rather than calibrated captures. It makes the problem highly under specified, since an object can look quite different from different angles and from different light directions. Yet many solutions have been attempted under varying assumptions, and the most promising solutions to date are those which use supervised deep learning techniques. The network is first trained with a large number of synthetically created images of surfaces, usually planar, with known values for material properties and then asked to predict the properties for image(s) of a new object. While the results obtained are impressive as shown through renders of the input object using recovered material properties, there is a problem in the accuracy of the recovered properties. Material properties get entangled, specifically the diffuse and specular reflectance behaviors. Such inaccuracies would hinder various down stream applications which use these properties. In this position paper we present this property entanglement problem. First, we demonstrate the problem through various property map outputs obtained by running a state of the deep learning solution. Next we analyse the present solutions, and argue that the main reason for this entanglement is the way the loss function is defined when training the network. Lastly, we propose potential directions that could be pursued to alleviate this problem.
Quality Assurance Based on Descriptive and Parsimonious Appearance Models
(The Eurographics Association, 2015) Nielsen, J. B.; Eiriksson, E. R.; Kristensen, R. L.; Wilm, J.; Frisvad, J. R.; Conradsen, K.; Aanæs, H.; Reinhard Klein and Holly Rushmeier
In this positional paper, we discuss the potential benefits of using appearance models in additive manufacturing, metal casting, wind turbine blade production, and 3D content acquisition. Current state of the art in acquisition and rendering of appearance cannot easily be used for quality assurance in these areas. The common denominator is the need for descriptive and parsimonious appearance models. By 'parsimonious' we mean with few parameters so that a model is useful both for fast acquisition, robust fitting, and fast rendering of appearance. The word 'descriptive' refers to the fact that a model should represent the main features of the acquired appearance data. The solution we propose is to reduce the degrees of freedom by greater use of multivariate statistics.
Statistical Characterization of Surface Reflectance
(The Eurographics Association, 2014) Havran, Vlastimil; Sbert, Mateu; Reinhard Klein and Holly Rushmeier
The classification of surface reflectance functions as diffuse, specular, and glossy has been introduced by Heckbert more than two decades ago. Many rendering algorithms are dependent on such a classification, as different kinds of light transport will be handled by specialized methods, for example caustics require specular bounce or refraction. Due to the increasing wealth of surface reflectance models including those based on measured data, it has not been possible to keep such a characterization simple. Each surface reflectance model is mostly handled separately, or alternatively, the rendering algorithm restricts itself to the use of some subset of reflectance models. We suggest a characterization for arbitrary surface reflectance representation by standard statistical tools, namely normalized variance known as Squared-Coefficient-of-Variation (SCV).We show by videos that there is even a weak perceptual correspondence with the proposed reflectance characterization, when we use monochromatic surface reflectance and the images are normalized so they have the unit albedo.
Towards a Practical Gamut of Appearance Acquisition
(The Eurographics Association, 2013) Fuchs, M.; Koch, S.; Gieseke, L.; Mozer, F.; Eberhardt, B.; Reinhard Klein and Holly Rushmeier
We propose discussing the performance of appearance modeling in terms of supported material and illumination gamut. While we have a precise understanding of the cost of any given appearance modeling method, performance is intrinsically hard to express without standardized material and illumination test scenarios. This lack of vocabulary hampers comparability between alternative approaches as well as the communication with community outsiders.
Towards Sparse and Multiplexed Acquisition of Material BTFs
(The Eurographics Association, 2017) Brok, Dennis den; Weinmann, Michael; Klein, Reinhard; Reinhard Klein and Holly Rushmeier
We present preliminary results on our effort to combine sparse and illumination-multiplexed acquisition of bidirectional texture functions (BTFs) for material appearance. Both existing acquisition paradigms deal with a single specific problem: the desire to reduce either the number of images to be obtained while maintaining artifact-free renderings, or the shutter times required to capture the full dynamic range of a material's appearance. These problems have so far been solved by means of data-driven models. We demonstrate that the way these models are derived prevents combined sparse and multiplexed acquisition, and introduce a novel model that circumvents this obstruction. As a result, we achieve acquisition times on the order of minutes in comparison to the few hours required with sparse acquisition or multiplexed illumination.

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