Poisson Surface Reconstruction

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dc.contributor.authorKazhdan, Michaelen_US
dc.contributor.authorBolitho, Matthewen_US
dc.contributor.authorHoppe, Huguesen_US
dc.contributor.editorAlla Sheffer and Konrad Polthieren_US
dc.date.accessioned2014-01-29T08:14:02Z
dc.date.available2014-01-29T08:14:02Z
dc.date.issued2006en_US
dc.description.abstractWe 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.en_US
dc.description.seriesinformationSymposium on Geometry Processingen_US
dc.identifier.isbn3-905673-24-Xen_US
dc.identifier.issn1727-8384en_US
dc.identifier.urihttps://doi.org/10.2312/SGP/SGP06/061-070en_US
dc.publisherThe Eurographics Associationen_US
dc.titlePoisson Surface Reconstructionen_US
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SGP06: Eurographics Symposium on Geometry Processing