A Low-Dimensional Perceptual Space for Intuitive BRDF Editing (original) (raw)
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Figure 1: Our approach enables intuitive appearance editing of high-level perceptual attributes. Our framework takes as an input a single image of an object (top) and produces high-quality edits of material attributes such as glossy or metallic, while preserving the geometrical structure and details (bottom). The"+" and "-" indicate whether the target high-level perceptual attribute is increased or decreased.
Photo editing software allows digital images to be blurred, warped or re-colored at the touch of a button. However, it is not currently possible to change the material appearance of an object except by painstakingly painting over the appropriate pixels. Here we present a method for automatically replacing one material with another, completely different material, starting with only a single high dynamic range image as input. Our approach exploits the fact that human vision is surprisingly tolerant of certain (sometimes enormous) physical inaccuracies, while being sensitive to others. By adjusting our simulations to be careful about those aspects to which the human visual system is sensitive, we are for the rst time able to demonstrate signicant material changes on the basis of a single photograph as input.
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Abstract Measured materials are used in computer graphics to enhance the realism of synthetic images. They are often approximated with analytical models to improve storage efficiency and allow for importance sampling. However, the error metrics used in the optimization procedure do not have a perceptual basis and the obtained results do not always correspond to the best visual match. In this paper we present a first steps towards creating a perceptually-based metric for BRDF modeling.
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During the last few years, many different techniques for measuring material appearance have arisen. These advances have allowed the creation of large public datasets, and new methods for editing BRDFs of captured appearance have been proposed. However, these methods lack intuitiveness and are hard to use for novice users. In order to overcome these limitations, Serrano et al. [SGM∗16] recently proposed an intuitive space for editing captured appearance. They make use of a representation of the BRDF based on a combination of principal components (PCA) to reduce dimensionality, and then map these components to perceptual attributes. This PCA representation is biased towards specular materials and fails to represent very diffuse BRDFs, therefore producing unpleasant artifacts when editing. In this paper, we build on top of their work and propose to use two separate PCA bases for representing specular and diffuse BRDFs, and map each of these bases to the perceptual attributes. This allo...
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Figure 1: We propose a method to control and improve the appearance of an existing material (left) by transferring the appearance of materials in one or multiple target photo(s) (center) to the existing material. The augmented material (right) combines the coarse structure from the original material with the fine-scale appearance of the target(s) and preserve the input tileability. Our method can also transfer appearance from materials from different types by spatial control. This enables a simple workflow to make existing materials more realistic using readily-available images or photos.
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Bidirectional Reflectance Distribution Functions (BRDFs) are pivotal to the perceived realism in image synthesis. While measured BRDF datasets are available, reflectance functions are most of the time approximated by analytical formulas for storage efficiency reasons. These approximations are often obtained by minimizing metrics such as L2—or weighted quadratic—distances, but these metrics do not usually correlate well with perceptual quality when the BRDF is used in a rendering context, which motivates a perceptual study. The contributions of this paper are threefold. First, we perform a large‐scale user study to assess the perceptual quality of 2026 BRDF approximations, resulting in 84138 judgments across 1005 unique participants. We explore this dataset and analyze perceptual scores based on material type and illumination. Second, we assess nine analytical BRDF models in their ability to approximate tabulated BRDFs. Third, we assess several image‐based and BRDF‐based (Lp, optimal...
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For many years appearance models in computer graphics focused on general models for reflectance functions coupled with texture maps. Recently it has been recognized that even very common materials such as hair, skin, fabric, and rusting metal require more sophisticated models to appear realistic. We will begin by briefly reviewing basic reflectance models and the use of texture maps. We then describe common themes in advanced material models that include combining the effects of layers, groups of particles and/or fibers. We will survey the detailed models necessary needed to model materials such as skin (including pigmentation, pores, subsurface scattering), plants (including internal structure) and automotive paints (including color flop and sparkle). We will then treat the modeling of complex appearance due to aging and weathering processes. A general taxonomy of effects will be presented, as well as methods to simulate and to capture these effects. We close with a summary of current trends in material appearance research and a discussion of existing and needed resources.
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Many representations and rendering techniques have been proposed for presenting material appearance in computer graphics. One outstanding problem is evaluating their accuracy. In this paper, we propose assessing accuracy by comparing human judgements of material attributes made when viewing a computer graphics rendering to those made when viewing a physical sample of the same material. We demonstrate this approach using 16 diverse physical material samples distributed to researchers at the MAM 2014 workshop. We performed two psychophysical experiments. In the first experiment we examined how consistently subjects rate a set of twelve visual, tactile and subjective attributes of individual physical material specimens. In the second experiment, we asked subjects to assess the same attributes for identical materials rendered as BTFs under point-light and environment illuminations. By analyzing obtained data, we identified which material attributes and material types are judged consistently and to what extent the computer graphics representation conveyed the experience of viewing physical material appearance.
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