Browsing by Author "Alliez, Pierre"

Now showing 1 - 6 of 6
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    Delaunay Meshing and Repairing of NURBS Models
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Xiao, Xiao; Alliez, Pierre; Busé, Laurent; Rineau, Laurent; Digne, Julie and Crane, Keenan
    CAD models represented by NURBS surface patches are often hampered with defects due to inaccurate representations of trimming curves. Such defects make these models unsuitable to the direct generation of valid volume meshes, and often require trial-and-error processes to fix them. We propose a fully automated Delaunay-based meshing approach which can mesh and repair simultaneously, while being independent of the input NURBS patch layout. Our approach proceeds by Delaunay filtering and refinement, in which trimmed areas are repaired through implicit surfaces. Beyond repair, we demonstrate its capability to smooth out sharp features, defeature small details, and mesh multiple domains in contact.
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    Editorial
    (Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Alliez, Pierre; Hauser, Helwig; Hauser, Helwig and Alliez, Pierre
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    EUROGRAPHICS 2019: CGF 38-2 Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Alliez, Pierre; Pellacini, Fabio; Alliez, Pierre and Pellacini, Fabio
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    Feature-Preserving Offset Mesh Generation from Topology-Adapted Octrees
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Zint, Daniel; Maruani, Nissim; Rouxel-Labbé, Mael; Alliez, Pierre; Memari, Pooran; Solomon, Justin
    We introduce a reliable method to generate offset meshes from input triangle meshes or triangle soups. Our method proceeds in two steps. The first step performs a Dual Contouring method on the offset surface, operating on an adaptive octree that is refined in areas where the offset topology is complex. Our approach substantially reduces memory consumption and runtime compared to isosurfacing methods operating on uniform grids. The second step improves the output Dual Contouring mesh with an offset-aware remeshing algorithm to reduce the normal deviation between the mesh facets and the exact offset. This remeshing process reconstructs concave sharp features and approximates smooth shapes in convex areas up to a user-defined precision. We show the effectiveness and versatility of our method by applying it to a wide range of input meshes. We also benchmark our method on the Thingi10k dataset: watertight and topologically 2-manifold offset meshes are obtained for 100% of the cases.
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    Progressive Discrete Domains for Implicit Surface Reconstruction
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Zhao, Tong; Alliez, Pierre; Boubekeur, Tamy; Busé, Laurent; Thiery, Jean-Marc; Digne, Julie and Crane, Keenan
    Many global implicit surface reconstruction algorithms formulate the problem as a volumetric energy minimization, trading data fitting for geometric regularization. As a result, the output surfaces may be located arbitrarily far away from the input samples. This is amplified when considering i) strong regularization terms, ii) sparsely distributed samples or iii) missing data. This breaks the strong assumption commonly used by popular octree-based and triangulation-based approaches that the output surface should be located near the input samples. As these approaches refine during a pre-process, their cells near the input samples, the implicit solver deals with a domain discretization not fully adapted to the final isosurface. We relax this assumption and propose a progressive coarse-to-fine approach that jointly refines the implicit function and its representation domain, through iterating solver, optimization and refinement steps applied to a 3D Delaunay triangulation. There are several advantages to this approach: the discretized domain is adapted near the isosurface and optimized to improve both the solver conditioning and the quality of the output surface mesh contoured via marching tetrahedra.
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    A Survey of Surface Reconstruction from Point Clouds
    (© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Berger, Matthew; Tagliasacchi, Andrea; Seversky, Lee M.; Alliez, Pierre; Guennebaud, Gaël; Levine, Joshua A.; Sharf, Andrei; Silva, Claudio T.; Chen, Min and Zhang, Hao (Richard)
    The area of surface reconstruction has seen substantial progress in the past two decades. The traditional problem addressed by surface reconstruction is to recover the digital representation of a physical shape that has been scanned, where the scanned data contain a wide variety of defects. While much of the earlier work has been focused on reconstructing a piece‐wise smooth representation of the original shape, recent work has taken on more specialized priors to address significantly challenging data imperfections, where the reconstruction can take on different representations—not necessarily the explicit geometry. We survey the field of surface reconstruction, and provide a categorization with respect to priors, data imperfections and reconstruction output. By considering a holistic view of surface reconstruction, we show a detailed characterization of the field, highlight similarities between diverse reconstruction techniques and provide directions for future work in surface reconstruction.The area of surface reconstruction has seen substantial progress in the past two decades. The traditional problem addressed by surface reconstruction is to recover the digital representation of a physical shape that has been scanned, where the scanned data contain a wide variety of defects. While much of the earlier work has been focused on reconstructing a piece‐wise smooth representation of the original shape, recent work has taken on more specialized priors to address significantly challenging data imperfections, where the reconstruction can take on different representations—not necessarily the explicit geometry