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    Shape-Up: Shaping Discrete Geometry with Projections

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    Date
    2012
    Author
    Bouaziz, Sofien
    Deuss, Mario
    Schwartzburg, Yuliy
    Weise, Thibaut
    Pauly, Mark
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    Abstract
    We introduce a unified optimization framework for geometry processing based on shape constraints. These constraints preserve or prescribe the shape of subsets of the points of a geometric data set, such as polygons, one-ring cells, volume elements, or feature curves. Our method is based on two key concepts: a shape proximity function and shape projection operators. The proximity function encodes the distance of a desired least-squares fitted elementary target shape to the corresponding vertices of the 3D model. Projection operators are employed to minimize the proximity function by relocating vertices in a minimal way to match the imposed shape constraints. We demonstrate that this approach leads to a simple, robust, and efficient algorithm that allows implementing a variety of geometry processing applications, simply by combining suitable projection operators. We show examples for computing planar and circular meshes, shape space exploration, mesh quality improvement, shape-preserving deformation, and conformal parametrization. Our optimization framework provides a systematic way of building new solvers for geometry processing and produces similar or better results than state-of-the-art methods.
    BibTeX
    @article {10.1111:j.1467-8659.2012.03171.x,
    journal = {Computer Graphics Forum},
    title = {{Shape-Up: Shaping Discrete Geometry with Projections}},
    author = {Bouaziz, Sofien and Deuss, Mario and Schwartzburg, Yuliy and Weise, Thibaut and Pauly, Mark},
    year = {2012},
    publisher = {The Eurographics Association and Blackwell Publishing Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/j.1467-8659.2012.03171.x}
    }
    URI
    http://dx.doi.org/10.1111/j.1467-8659.2012.03171.x
    Collections
    • 31-Issue 5
    • SGP12: Eurographics Symposium on Geometry Processing

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