SGP07: Eurographics Symposium on Geometry Processing

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https://diglib.eg.org/handle/10.2312/440

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Browsing SGP07: Eurographics Symposium on Geometry Processing by Subject "Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Line and Curve Generation"

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    Bayesian Surface Reconstruction via Iterative Scan Alignment to an Optimized Prototype
    (The Eurographics Association, 2007) Huang, Qi-Xing; Adams, Bart; Wand, Michael; Alexander Belyaev and Michael Garland
    This paper introduces a novel technique for joint surface reconstruction and registration. Given a set of roughly aligned noisy point clouds, it outputs a noise-free and watertight solid model. The basic idea of the new technique is to reconstruct a prototype surface at increasing resolution levels, according to the registration accuracy obtained so far, and to register all parts with this surface. We derive a non-linear optimization problem from a Bayesian formulation of the joint estimation problem. The prototype surface is represented as a partition of unity implicit surface, which is constructed from piecewise quadratic functions defined on octree cells and blended together using B-spline basis functions, allowing the representation of objects with arbitrary topology with high accuracy. We apply the new technique to a set of standard data sets as well as especially challenging real-world cases. In practice, the novel prototype surface based joint reconstruction-registration algorithm avoids typical convergence problems in registering noisy range scans and substantially improves the accuracy of the final output.
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    GPU-assisted Positive Mean Value Coordinates for Mesh Deformations
    (The Eurographics Association, 2007) Lipman, Yaron; Kopf, Johannes; Cohen-Or, Daniel; Levin, David; Alexander Belyaev and Michael Garland
    In this paper we introduce positive mean value coordinates (PMVC) for mesh deformation. Following the observations of Joshi et al. [JMD*07] we show the advantage of having positive coordinates. The control points of the deformation are the vertices of a "cage" enclosing the deformed mesh. To define positive mean value coordinates for a given vertex, the visible portion of the cage is integrated over a sphere. Unlike MVC [JSW05], PMVC are computed numerically. We show how the PMVC integral can be efficiently computed with graphics hardware. While the properties of PMVC are similar to those of Harmonic coordinates [JMD*07], the setup time of the PMVC is only of a few seconds for typical meshes with 30K vertices. This speed-up renders the new coordinates practical and easy to use.