86 research outputs found

    ReMESH: An interactive and user-friendly environment for remeshing surface triangulations

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    Research and software development involving geometry processing are often slowed down by the absence of suitable models for testing and benchmark purposes. In particular, when dealing with triangle meshes, a researcher may need to check the behavior of a new algorithm on several particular cases. In most situations, the test model is easily conceivable in mind but, at actual design time, its formalization turns out to be a much harder task than expected. Also, simple modifications over an existing triangle mesh may become a tedious work without a suitable interactive environment. In order to simplify the remeshing of existing models, we have developed a tool to interactively edit manifold triangle meshes, mostly through user friendly actions such as mouse clicks and drags

    From 3D Models to 3D Prints: an Overview of the Processing Pipeline

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    Due to the wide diffusion of 3D printing technologies, geometric algorithms for Additive Manufacturing are being invented at an impressive speed. Each single step, in particular along the Process Planning pipeline, can now count on dozens of methods that prepare the 3D model for fabrication, while analysing and optimizing geometry and machine instructions for various objectives. This report provides a classification of this huge state of the art, and elicits the relation between each single algorithm and a list of desirable objectives during Process Planning. The objectives themselves are listed and discussed, along with possible needs for tradeoffs. Additive Manufacturing technologies are broadly categorized to explicitly relate classes of devices and supported features. Finally, this report offers an analysis of the state of the art while discussing open and challenging problems from both an academic and an industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and Innovation action; Grant agreement N. 68044

    A new method for simplification and compression of 3D meshes

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    We focus on the lossy compression of manifold triangle meshes. Our SwingWrapper approach partitions the surface of an original mesh M into simply-connected regions, called triangloids. We compute a new mesh M\u27. Each triangle of M\u27 is a close approximation of a pseudo-triangle of M. By construction, the connectivity of M\u27 is fairly regular and can be compressed to less than a bit per triangle using EdgeBreaker or one of the other recently developed schemes. The locations of the vertices of M\u27 are compactly encoded with our new prediction scheme, which uses a single correction parameter per vertex. For example, a variety of popular models retiled with our approach yield 10 times fewer triangles without exceeding an error of 1% of the radius of the bounding ball. Vertices of M\u27 are encoded with an average of 6 bits, which results in a total storage of 0.4 bits per triangle of the original mesh. The proposed solution may also be used to encode crude meshes for adaptive transmission and for controlling subdivision surfaces

    Normal Umbrella: A new primitive for triangulating parametric surfaces

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    Typical methods for the triangulation of parametric surfaces use a sampling of the parameter space, and the wrong choice of parameterization can spoil a triangulation or even cause the algorithm to fail. We present a new method that uses a local tessellation primitive for almost-uniformly sampling and triangulating a surface, so that its parameterization becomes irrelevant. If sampling density or triangle shape has to be adaptive, the uniform mesh can be used either as an initial coarse mesh for a refinement process, or as a fine mesh to be reduced

    SHREC08 Entry: Report of the Stability Track on Watertight Models

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    In this report we present the results of the Stability on Watertight Models Track. The aim of this track is to evaluate the stability of algorithms with respect to input perturbations that modify the representation of the object without changing its overall shape significantly. Examples of these perturbations include geometric noise, varying sampling patterns, small shape deformations and topological noise

    Surface Remeshing and Applications

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    Due to the focus of popular graphic accelerators, triangle meshes remain the primary representation for 3D surfaces. They are the simplest form of interpolation between surface samples, which may have been acquired with a laser scanner, computed from a 3D scalar field resolved on a regular grid, or identified on slices of medical data. Typical methods for the generation of triangle meshes from raw data attempt to lose as less information as possible, so that the resulting surface models can be used in the widest range of scenarios. When such a general-purpose model has to be used in a particular application context, however, a pre-processing is often worth to be considered. In some cases, it is convenient to slightly modify the geometry and/or the connectivity of the mesh, so that further processing can take place more easily. Other applications may require the mesh to have a pre-defined structure, which is often different from the one of the original general-purpose mesh. The central focus of this thesis is the automatic remeshing of highly detailed surface triangulations. Besides a thorough discussion of state-of-the-art applications such as real-time rendering and simulation, new approaches are proposed which use remeshing for topological analysis, flexible mesh generation and 3D compression. Furthermore, innovative methods are introduced to post-process polygonal models in order to recover information which was lost, or hidden, by a prior remeshing process. Besides the technical contributions, this thesis aims at showing that surface remeshing is much more useful than it may seem at a first sight, as it represents a nearly fundamental step for making several applications feasible in practice

    Edge-Sharpener: A geometric filter for recovering sharp features in uniform triangulations

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    3D scanners, iso-surface extraction procedures, and several recent geometric compression schemes sample surfaces of 3D shapes in a regular fashion, without any attempt to align the samples with the sharp edges and corners of the original shape. Consequently, the interpolating triangle meshes chamfer these sharp features and thus exhibit significant errors. The new Edge-Sharpener filter introduced here identifies the chamfer edges and subdivides them and their incident triangles by inserting new vertices and by forcing these vertices to lie on intersections of planes that locally approximate the smooth surfaces that meet at these sharp features. This post-processing significantly reduces the error produced by the initial sampling process. For example, we have observed that the L2 error introduced by the SwingWrapper9 remeshing-based compressor can be reduced down to a fifth by executing Edge-Sharpener after decompression, with no additional information

    Parametric shape optimization for combined additive–subtractive manufacturing

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s11837-019-03886-xIn industrial practice, additive manufacturing (AM) processes are often followed by post-processing operations such as heat treatment, subtractive machining, milling, etc., to achieve the desired surface quality and dimensional accuracy. Hence, a given part must be 3D-printed with extra material to enable this finishing phase. This combined additive/subtractive technique can be optimized to reduce manufacturing costs by saving printing time and reducing material and energy usage. In this work, a numerical methodology based on parametric shape optimization is proposed for optimizing the thickness of the extra material, allowing for minimal machining operations while ensuring the finishing requirements. Moreover, the proposed approach is complemented by a novel algorithm for generating inner structures to reduce the part distortion and its weight. The computational effort induced by classical constrained optimization methods is alleviated by replacing both the objective and constraint functions by their sparse grid surrogates. Numerical results showcase the effectiveness of the proposed approach.Peer ReviewedPostprint (published version
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