MAM2018: Eurographics Workshop on Material Appearance Modeling

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https://diglib.eg.org/handle/10.2312/2632655

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Browsing MAM2018: Eurographics Workshop on Material Appearance Modeling by Subject "I.3.3 [Computer Graphics]"

Now showing 1 - 4 of 4
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    Deep Dual Loss BRDF Parameter Estimation
    (The Eurographics Association, 2018) Boss, Mark; Groh, Fabian; Herholz, Sebastian; Lensch, Hendrik P. A.; Reinhard Klein and Holly Rushmeier
    Surface parameter estimation is an essential field in computer games and movies. An exact representation of a real-world surface allows for a higher degree of realism. Capturing or artistically creating these materials is a time-consuming process. We propose a method which utilizes an encoder-decoder Convolutional Neural Network (CNN) to extract parameters for the Bidirectional Reflectance Distribution Function (BRDF) automatically from a sparse sample set. This is done by implementing a differentiable renderer, which allows for a loss backpropagation of rendered images. This photometric loss is essential because defining a numerical BRDF distance metric is difficult. A second loss is added, which compares the parameters maps directly. Therefore, the statistical properties of the BRDF model are learned, which reduces artifacts in the predicted parameters. This dual loss principal improves the result of the network significantly. Opposed to previous means this method retrieves information of the whole surface as spatially varying BRDF (SVBRDF) parameters with a sufficiently high resolution for intended real-world usage. The capture process for materials only requires five known light positions with a fixed camera position. This reduces the scanning time drastically, and a material sample can be obtained in seconds with an automated system.
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    Image-based Fitting of Procedural Yarn Models
    (The Eurographics Association, 2018) Saalfeld, Alina; Reibold, Florian; Dachsbacher, Carsten; Reinhard Klein and Holly Rushmeier
    While common in real life, rendering fiber and cloth accurately is challenging. Recent fiber-based, procedural rendering approaches proved to be able to capture a great amount of details of real yarn. However, the current automatic method of fitting the model parameters is expensive and inaccessible as it relies on micro CT scans of the reference yarn. The alternative is to have an artist fit the parameters by hand, which is impractical because of the large number of parameters. We present a proof-of-concept for a purely image-based approach to fit the parameters of a procedural yarn model. Using gradient descent and pixel-based loss functions, we are able to extract a subset of the model parameters from rendered images with known parameters. The appearance of the fitted models is nearly indistinguishable from the reference images.
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    A Simple Diffuse Fluorescent BBRRDF Model
    (The Eurographics Association, 2018) Jung, Alisa; Hanika, Johannes; Marschner, Steve; Dachsbacher, Carsten; Reinhard Klein and Holly Rushmeier
    Fluorescence - the effect of a photon being absorbed at one wavelength and re-emitted at another - is present in many common materials such as clothes and paper. Yet there has been little research in rendering or modeling fluorescent surfaces. We discuss the design decisions leading to a simple model for a diffuse fluorescent BBRRDF (bispectral bidirectional reflection and reradiation distribution function). In contrast to reradiation matrix based models our model is continuous in wavelength space. It can be parameterized by artificially designed spectra as well as by many publicly available physical measurements. It combines fluorescence and non-fluorescent reflectance, as most real-world materials are not purely fluorescent but also reflect some light without changing its wavelength. With its simple parameterization the BBRRDF is intended as a starting point for any physically based spectral rendering system aiming to simulate fluorescence. To that end we show how to continuously sample both incident and exitant wavelengths from our BBRRDF which makes it suitable for bidirectional transport, and we discuss energy and photon conservation in the context of fluorescence.
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    Towards a Principled Kernel Prediction for Spatially Varying BSSRDFs
    (The Eurographics Association, 2018) Elek, Oskar; Krivánek, Jaroslav; Reinhard Klein and Holly Rushmeier
    While the modeling of sub-surface translucency using homogeneous BSSRDFs is an established industry standard, applying the same approach to heterogeneous materials is predominantly heuristical. We propose a more principled methodology for obtaining and evaluating a spatially varying BSSRDF, on the basis of the volumetric sub-surface structure of the simulated material. The key ideas enabling this are a simulation-data driven kernel for aggregating the spatially varying material parameters, and a structure-preserving decomposition of the sub-surface transport into a local and a global component. Our current results show significantly improved accuracy for planar materials with spatially varying scattering albedo, with added discussion about extending the approach for general geometries and full heterogeneity of the material parameters.