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Now showing 1 - 10 of 23
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    A Preliminary Analysis of Methods for Curvature Estimation on Surfaces With Local Reliefs
    (The Eurographics Association, 2019) Moscoso Thompson, Elia; Biasotti, Silvia; Cignoni, Paolo and Miguel, Eder
    Curvature estimation is very popular in geometry processing for the analysis of local surface variations. Despite the large number of methods, no quantitative nor qualitative studies have been conducted for a comparative analysis of the different algorithms on surfaces with small geometric variations, such as chiselled or relief surfaces. In this work we compare eight curvature estimation methods that are commonly adopted by the computer graphics community on a number of triangle meshes derived from scans of surfaces with local reliefs.
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    Automatic Step Size Relaxation in Sphere Tracing
    (The Eurographics Association, 2023) Bán, Róbert; Valasek, Gábor; Babaei, Vahid; Skouras, Melina
    We propose a robust auto-relaxed sphere tracing method that automatically scales its step sizes based on data from previous iterations. It possesses a scalar hyperparemeter that is used similarly to the learning rate of gradient descent methods. We show empirically that this scalar degree of freedom has a smaller effect on performance than the step-scale hyperparameters of concurrent sphere tracing variants. Additionally, we compare the performance of our algorithm to these both on procedural and discrete signed distance input and show that it outperforms or performs up to par to the most efficient method, depending on the limit on iteration counts. We also verify that our method takes significantly fewer robustness-preserving sphere trace fallback steps, as it generates fewer invalid, over-relaxed step sizes.
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    Mesh Smoothing for Teaching GLSL Programming
    (The Eurographics Association, 2022) Ilinkin, Ivaylo; Bourdin, Jean-Jacques; Paquette, Eric
    This paper shares ideas for effective assignment that can be used to introduce a number of advanced GLSL concepts including shader storage buffer objects, transform feedback, and compute shaders. The assignment is based on published research on mesh smoothing which serves as a motivating factor and offers a sense of accomplishment.
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    Smooth Blended Subdivision Shading
    (The Eurographics Association, 2018) Bakker, Jelle; Barendrecht, Pieter J.; Kosinka, Jiri; Diamanti, Olga and Vaxman, Amir
    The concept known as subdivision shading aims at improving the shading of subdivision surfaces. It is based on the subdivision of normal vectors associated with the control net of the surface. By either using the resulting subdivided normal field directly, or blending it with the normal field of the limit surface, renderings of higher visual smoothness can be obtained. In this work we propose a different and more versatile approach to blend the two normal fields, yielding not only better results, but also a proof that our blended normal field is C1.
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    Data-driven Garment Pattern Estimation from 3D Geometries
    (The Eurographics Association, 2021) Goto, Chihiro; Umetani, Nobuyuki; Theisel, Holger and Wimmer, Michael
    Three-dimensional scanning technology recently becomes widely available to the public. However, it is difficult to simulate clothing deformation from the scanned people because scanned data lacks information required for the clothing simulation. In this paper, we present a technique to estimate clothing patterns from a scanned person in cloth. Our technique uses image-based deep learning to estimate the type of pattern on the projected image. The key contribution is converting image-based inference into three-dimensional clothing pattern estimation. We evaluate our technique by applying our technique to an actual scan.
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    Neurosymbolic Models for Computer Graphics
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Ritchie, Daniel; Guerrero, Paul; Jones, R. Kenny; Mitra, Niloy J.; Schulz, Adriana; Willis, Karl D. D.; Wu, Jiajun; Bousseau, Adrien; Theobalt, Christian
    Procedural models (i.e. symbolic programs that output visual data) are a historically-popular method for representing graphics content: vegetation, buildings, textures, etc. They offer many advantages: interpretable design parameters, stochastic variations, high-quality outputs, compact representation, and more. But they also have some limitations, such as the difficulty of authoring a procedural model from scratch. More recently, AI-based methods, and especially neural networks, have become popular for creating graphic content. These techniques allow users to directly specify desired properties of the artifact they want to create (via examples, constraints, or objectives), while a search, optimization, or learning algorithm takes care of the details. However, this ease of use comes at a cost, as it's often hard to interpret or manipulate these representations. In this state-of-the-art report, we summarize research on neurosymbolic models in computer graphics: methods that combine the strengths of both AI and symbolic programs to represent, generate, and manipulate visual data. We survey recent work applying these techniques to represent 2D shapes, 3D shapes, and materials & textures. Along the way, we situate each prior work in a unified design space for neurosymbolic models, which helps reveal underexplored areas and opportunities for future research.
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    Tetrahedral Interpolation on Regular Grids
    (The Eurographics Association, 2021) Bán, Róbert; Valasek, Gábor; Bittner, Jirí and Waldner, Manuela
    This work proposes the use of barycentric interpolation on enclosing simplices of sample points to infer a reconstructed function from discrete data. In particular, we compare the results of trilinear and tetrahedral interpolation over regular 3D grids of second order spherical harmonics (SH) light probes. In general, tetrahedral interpolation only requires four data samples per query in contrast to the 8 samples necessary for trilinear interpolation, at the expense of a more expensive weight computation. Our tetrahedral implementation subdivides the cubical cells into six tetrahedra and uses the barycentric coordinates of the query position as weights to blend the probe data. We show that barycentric coordinates can be calculated efficiently in shaders for our particular tetrahedral decomposition of the cube, resulting only in simple arithmetic and conditional move operations.
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    Growing Circles: A Region Growing Algorithm for Unstructured Grids and Non-aligned Boundaries
    (The Eurographics Association, 2018) Dabbaghchian, Saeed; Jain, Eakta and Kosinka, Jirí
    Detecting the boundaries of an enclosed region is a problem which arises in some applications such as the human upper airway modeling. Using of standard algorithms fails because of the inevitable errors, i.e. gaps and overlaps between the surrounding boundaries. Growing circles is an automatic approach to address this problem. A circle is centered inside the region and starts to grow by increasing its radius. Its growth is limited either by the surrounding boundaries or by reaching its maximum radius. To deal with complex shapes, many circles are used in which each circle partially reconstructs the region, and the whole region is determined by the union of these partial regions. The center of the circles and their maximum radius are calculated adaptively. It is similar to the region growing algorithm which is widely used in image processing applications. However, it works for unstructured grids as well as Cartesian ones. As an application of the method, it is applied to detect the boundaries of the upper airway cross-sections.
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    Procedural Bridges-and-pillars Support Generation
    (The Eurographics Association, 2022) Freire, Marco; Hornus, Samuel; Perchy, Salim; Lefebvre, Sylvain; Pelechano, Nuria; Vanderhaeghe, David
    Additive manufacturing requires support structures to fabricate parts with overhangs. In this paper, we revisit a known support structure based on bridges-and-pillars (see Figure 1). The support structures are made of vertical pillars supporting horizontal bridges. Their scaffolding structure makes them stable and reliable to print. However, the algorithm heuristic search does not scale well and is prone to produce contacts with the parts, leaving scars after removal. We propose a novel algorithm for this type of supports, focusing on avoiding unnecessary contacts with the part as much as possible. Our approach builds upon example-based model synthesis to enable early detection of collision-free passages as well as non-reachable regions.
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    Sparse Ferguson-Hermite Signed Distance Fields
    (The Eurographics Association, 2023) Bán, Róbert; Valasek, Gábor; Singh, Gurprit; Chu, Mengyu (Rachel)
    We investigate Hermite interpolation in the context of discrete signed distance field filtering. Our method uses tricubic Hermite interpolation to generate a C1 continuous approximation to the signed distance function of the input scene. Our representation is kept purely first order by setting the mixed partial derivatives to zero, similarly to how Ferguson constructed bicubic Hermite patches. Our scheme stores four scalars at each sample, the value of the signed distance function and its first three partial derivatives. We optimize storage by only storing voxels that enclose a volume boundary. We show that this provides both a significant reduction in storage and render times compared to a dense grid of Ferguson-Hermite samples. Moreover, our construct requires smaller storage than traditional zero order trilinearly filtered fields of the same visual quality, at the expense of performance.