Recent Submissions

  • Visual Assessments of Functional Maps 

    Melzi, S.; Marin, R.; Musoni, P.; Castellani, U.; Tarini, M. (The Eurographics Association, 2019)
    Shape-matching is one central topic in Geometry Processing, with numerous important applications in Computer Graphics and shape analysis, such as shape registration, shape interpolation, modeling, information transfer and ...
  • Adaptive Block Coordinate Descent for Distortion Minimization 

    Naitsat, Alexander; Zeevi, Yehoshua Y. (The Eurographics Association, 2019)
    We present a new unified algorithm for optimizing geometric energies and computing positively oriented simplicial mappings. Its major improvements over the state-of-the-art are: adaptive partition of vertices into coordinate ...
  • Solving Variational Problems Using Nonlinear Rotation-invariant Coordinates 

    Sassen, Josua; Heeren, Behrend; Hildebrandt, Klaus; Rumpf, Martin (The Eurographics Association, 2019)
    We consider Nonlinear Rotation-Invariant Coordinates (NRIC) representing triangle meshes with fixed combinatorics as a vector stacking all edge lengths and dihedral angles. Previously, conditions for the existence of vertex ...
  • Symposium on Geometry Processing 2019 – Posters: Frontmatter 

    Bommes, David; Huang, Hui (Eurographics Association, 2019)
  • Functional Maps on Product Manifolds 

    Rodolà, Emanuele; Lähner, Zorah; Bronstein, Alex M.; Bronstein, Michael M.; Solomon, Justin (The Eurographics Association, 2018)
    We consider the tasks of representing, analyzing and manipulating maps between shapes. We model maps as densities over the product manifold of the input shapes; these densities can be treated as scalar functions and therefore ...
  • Solving PDEs on Deconstructed Domains 

    Sellán, Silvia; Cheng, Herng Yi; Ma, Yuming; Dembowski, Mitchell; Jacobson, Alec (The Eurographics Association, 2018)
    When finding analytical solutions to Partial Differential Equations (PDEs) becomes impossible, it is useful to approximate them via a discrete mesh of the domain. Sometimes a robust triangular (2D) or tetrahedral (3D) mesh ...
  • Denoising of Point-clouds Based on Structured Dictionary Learning 

    Sarkar, Kripasindhu; Bernard, Florian; Varanasi, Kiran; Theobalt, Christian; Stricker, Didier (The Eurographics Association, 2018)
    We formulate the problem of point-cloud denoising in terms of a dictionary learning framework over square surface patches. Assuming that many of the local patches (in the unknown noise-free point-cloud) contain redundancies ...
  • Using Mathematical Morphology to Simplify Archaeological Fracture Surfaces 

    ElNaghy, Hanan; Dorst, Leo (The Eurographics Association, 2018)
    It is computationally expensive to fit the high-resolution 3D meshes of abraded fragments of archaeological artefacts in a collection. Therefore, simplification of fracture surfaces while preserving the fitting essentials ...
  • Out-of-core Resampling of Gigantic Point Clouds 

    Bletterer, Arnaud; Payan, Frédéric; Antonini, Marc; Meftah, Anis (The Eurographics Association, 2018)
    Nowadays, LiDAR scanners are able to capture complex scenes of real life, leading to extremely detailed point clouds. However, the amount of points acquired (several billions) and their distribution raise the problem of ...
  • Frontmatter: Symposium on Geometry Processing 2018 - Posters 

    Ju, Tao; Vaxman, Amir (The Eurographics Association, 2018)
  • Schrödinger Operator for Sparse Approximation of 3D Meshes 

    Choukroun, Yoni; Pai, Gautam; Kimmel, Ron (The Eurographics Association, 2017)
    We introduce a Schrödinger operator for spectral approximation of meshes representing surfaces in 3D. The operator is obtained by modifying the Laplacian with a potential function which defines the rate of oscillation of ...
  • PCR: A Geometric Cocktail for Triangulating Point Clouds Beautifully Without Angle Bounds 

    Leitão, Gonçalo N. V.; Gomes, Abel J. P. (The Eurographics Association, 2017)
    Reconstructing a triangulated surface from a point cloud through a mesh growing algorithm is a difficult problem, in largely because they use bounds for the admissible dihedral angle to decide on the next triangle to be ...
  • A Primal-to-Primal Discretization of Exterior Calculus on Polygonal Meshes 

    Ptackova, Lenka; Velho, Luiz (The Eurographics Association, 2017)
    Discrete exterior calculus (DEC) offers a coordinate-free discretization of exterior calculus especially suited for computations on curved spaces. We present an extended version of DEC on surface meshes formed by general ...
  • Localized Manifold Harmonics for Spectral Shape Analysis 

    Melzi, Simone; Rodolà, Emanuele; Castellani, Umberto; Bronstein, Michael M. (The Eurographics Association, 2017)
    The use of Laplacian eigenfunctions is ubiquitous in a wide range of computer graphics and geometry processing applications. In particular, Laplacian eigenbases allow generalizing the classical Fourier analysis to manifolds. ...
  • DepthCut: Improved Depth Edge Estimation Using Multiple Unreliable Channels 

    Guerrero, Paul; Winnemöller, Holger; Li, Wilmot; Mitra, Niloy J. (The Eurographics Association, 2017)
    In the context of scene understanding, a variety of methods exists to estimate different information channels from mono or stereo images, including disparity, depth, and normals. Although several advances have been reported ...
  • Symposium on Geometry Processing 2017: Frontmatter 

    Bærentzen, Jakob Andreas; Hildebrandt, Klaus (Eurographics Association, 2017)
  • Sequentially-Defined Compressed Modes via ADMM 

    Houston, Kevin (The Eurographics Association, 2017)
    The eigenfunctions of the discrete Laplace-Beltrami operator have played an important role in many aspects of geometry processing. Given the success of sparse representation methods in areas such as compressive sensing it ...
  • Deep Learning for Robust Normal Estimation in Unstructured Point Clouds 

    Boulch, Alexandre; Marlet, Renaud (The Eurographics Association and John Wiley & Sons Ltd., 2016)
    Normal estimation in point clouds is a crucial first step for numerous algorithms, from surface reconstruction and scene understanding to rendering. A recurrent issue when estimating normals is to make appropriate decisions ...
  • Mesh Statistics for Robust Curvature Estimation 

    Váša, Libor; Vaněček, Petr; Prantl, Martin; Skorkovská, Věra; Martínek, Petr; Kolingerová, Ivana (The Eurographics Association and John Wiley & Sons Ltd., 2016)
    While it is usually not difficult to compute principal curvatures of a smooth surface of sufficient differentiability, it is a rather difficult task when only a polygonal approximation of the surface is available, because ...
  • Disk Density Tuning of a Maximal Random Packing 

    Ebeida, Mohamed S.; Rushdi, Ahmad A.; Awad, Muhammad A.; Mahmoud, Ahmed H.; Yan, Dong-Ming; English, Shawn A.; Owens, John D.; Bajaj, Chandrajit L.; Mitchell, Scott A. (The Eurographics Association and John Wiley & Sons Ltd., 2016)
    We introduce an algorithmic framework for tuning the spatial density of disks in a maximal random packing, without changing the sizing function or radii of disks. Starting from any maximal random packing such as a Maximal ...

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