Reflectance and texture of real-world surfaces (original) (raw)
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Non-linear reflectance model for bidirectional texture function synthesis
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., 2004
A rough texture modelling involves a huge image data-set -the Bidirectional Texture Function (BTF). This 6-dimensional function depends on planar texture coordinates as well as on view and illumination angles. We propose a new non-linear reflectance model, based on a Lafortune reflectance model improvement, which restores all BTF database images independently for each view position and herewith significantly reduces stored BTF data size. The extension consists in introducing several spectral parameters for each BTF image which are linearly estimated in the second estimation step according to the original data. The model parameters are computed for every surface reflectance field contained in the original BFT data. This technique allows BTF data compression by the ratio 1:15 while the synthesised images are almost indiscernible from the originals. The method is universal, and easily implementable in a graphical hardware for purpose of real-time BTF rendering.
2015
Characterizing the appearance of real-world surfaces is a fundamental problem in multidimensional , computer vision and computer graphics. In this paper, we outline a unified perception-based approach to modeling of the appearance of materials for computer graphics and reflectometry. We discuss the differences and the common points of data analysis and modeling for BRDFs in both physical and in virtual application domains. We outline a mathematical framework that captures important problems in both types of application domains, and allows for application and performance comparisons of statistical and machine learning methods. For comparisons between methods, we use criteria that are relevant to both statistics and machine learning, as well as to both virtual and physical application domains. Additionally, we propose a class of multiple testing procedures to test a hypothesis that a material has diffuse reflection in a generalized sense. We treat a general case where the number of hy...
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009
An ever-growing number of real-world computer vision applications require classification, segmentation, retrieval, or realistic rendering of genuine materials. However, the appearance of real materials dramatically changes with illumination and viewing variations. Thus, the only reliable representation of material visual properties requires capturing of its reflectance in as wide range of light and camera position combinations as possible. This is a principle of the recent most advanced texture representation, the Bidirectional Texture Function (BTF). Multispectral BTF is a seven-dimensional function that depends on view and illumination directions as well as on planar texture coordinates. BTF is typically obtained by measurement of thousands of images covering many combinations of illumination and viewing angles. However, the large size of such measurements has prohibited their practical exploitation in any sensible application until recently. During the last few years, the first BTF measurement, compression, modeling, and rendering methods have emerged. In this paper, we categorize, critically survey, and psychophysically compare such approaches, which were published in this newly arising and important computer vision and graphics area.
A Survey of BRDF Models for Computer Graphics
To produce photo-realistic images in computer graphics, we must effectively describe the interactions between light and surfaces. In this paper, we focus on Bidirectional Reflectance Distribution Functions (BRDFs), which characterize these interactions. We survey on most BRDF representations introduced so far and we investigate their usage, importance and applications. We look at in detail their two important usages; in GPU-based real-time renderings and in renderings of metallic car paints.
Computer-aided appearance design based on BRDF measurements
Computer-Aided Design, 2011
This paper presents a comprehensive and efficient framework for computer-aided appearance design based on BRDF (bidirectional reflectance distribution function) measurements. It covers all stages of a new product development including acquisition, processing and modeling of reflectance data, interactive rendering and evaluation of material appearance, and manufacturing operations. The proposed method eliminates the need of making a real physical prototype by providing a reliable surface appearance design process in which he/she can faithfully simulate the final surface appearance in the early design stage of a product. In addition, it enables us to manufacture the coating surface the same as the computer simulated surface from the known coating specification. The accuracy test between a real sample and the computer simulated one demonstrates that the proposed method satisfies an acceptable level of accuracy for industrial applications. A case study has been conducted to evaluate the user preference on the surface appearance of a digital handheld device which contains a combination of different coating surfaces. The case study successfully demonstrates that the user preference can be identified using the proposed method while changing the combination of different coating surfaces represented by BRDFs considering factors such as surrounding environments and age groups.
Color Research & Application, 2015
A spectral-based method can acquire and represent the surface appearance of a given material physically correctly. But, it has drawbacks due to its high measurement cost and a long computation time in measuring, modeling, and rendering. In this article, we present spectral recovery and representation of spectral bidirectional reflectance distribution function (BRDF) from multispectral reflectance measurements in which we can render real appearance materials over a 3D model with accuracy and efficiency. First of all, an accurate spectral BRDF recovery algorithm, which transforms multispectral high dynamic range images into highly dense BRDFs in both a spectral and an angular domain, is proposed. Second, an efficient representation method is developed representing spectral BRDFs compactly using a factorization method and an adaptive spectral sampling method that uses a given error bound. The results show that the proposed method can compress the spectral BRDF data down by several hundred times while maintaining the given accuracy in colorimetric and spectral domains under a specific illuminant.
Efficient rendering of spatial bi-directional reflectance distribution functions
2002
Abstract We propose texture maps that contain at each texel all the parameters of a Lafortune representation BRDF as a compact, but quite general surface appearance representation. We describe a method for rendering such surfaces rapidly on current graphics hardware and demonstrate the method with real, measured surfaces and hand-painted surfaces. We also propose a method of rendering such spatial bi-directional reflectance distribution functions using prefiltered environment maps.
Image statistics for surface reflectance perception
Journal of the Optical Society of America A, 2008
Human observers can distinguish the albedo of real-world surfaces even when the surfaces are viewed in isolation, contrary to the Gelb effect. We sought to measure this ability and to understand the cues that might underlie it. We took photographs of complex surfaces such as stucco and asked observers to judge their diffuse reflectance by comparing them to a physical Munsell scale. Their judgments, while imperfect, were highly correlated with the true reflectance. The judgments were also highly correlated with certain image statistics, such as moment and percentile statistics of the luminance and subband histograms. When we digitally manipulated these statistics in an image, human judgments were correspondingly altered. Moreover, linear combinations of such statistics allow a machine vision system (operating within the constrained world of single surfaces) to estimate albedo with an accuracy similar to that of human observers. Taken together, these results indicate that some simple image statistics have a strong influence on the judgment of surface reflectance.
Image-based BRDF reconstruction
1999
Abstract This paper presents a method of reconstructing the parameters of a reflectance model from photograpbs of an object. We assume given object geometry and light source position, as well as a homogeneous reflectance function. We employ a semi-automatic camera calibration and reconstruct radiance values from several photograpbs using different exposure times. After choosing an appropriate set of samples from the radiance image, we compute the geometric parameters for each sample.