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    Poisson Surface Reconstruction

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    061-070.pdf (425.0Kb)
    Date
    2006
    Author
    Kazhdan, Michael
    Bolitho, Matthew
    Hoppe, Hugues
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    Abstract
    We show that surface reconstruction from oriented points can be cast as a spatial Poisson problem. This Poisson formulation considers all the points at once, without resorting to heuristic spatial partitioning or blending, and is therefore highly resilient to data noise. Unlike radial basis function schemes, our Poisson approach allows a hierarchy of locally supported basis functions, and therefore the solution reduces to a well conditioned sparse linear system. We describe a spatially adaptive multiscale algorithm whose time and space complexities are proportional to the size of the reconstructed model. Experimenting with publicly available scan data, we demonstrate reconstruction of surfaces with greater detail than previously achievable.
    BibTeX
    @inproceedings {10.2312:SGP:SGP06:061-070,
    booktitle = {Symposium on Geometry Processing},
    editor = {Alla Sheffer and Konrad Polthier},
    title = {{Poisson Surface Reconstruction}},
    author = {Kazhdan, Michael and Bolitho, Matthew and Hoppe, Hugues},
    year = {2006},
    publisher = {The Eurographics Association},
    ISSN = {1727-8384},
    ISBN = {3-905673-24-X},
    DOI = {10.2312/SGP/SGP06/061-070}
    }
    URI
    http://dx.doi.org/10.2312/SGP/SGP06/061-070
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    Theme by @mire NV
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