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dc.contributor.authorKazhdan, Mishaen_US
dc.contributor.authorChuang, Mingen_US
dc.contributor.authorRusinkiewicz, Szymonen_US
dc.contributor.authorHoppe, Huguesen_US
dc.contributor.editorJacobson, Alec and Huang, Qixingen_US
dc.date.accessioned2020-07-05T13:26:15Z
dc.date.available2020-07-05T13:26:15Z
dc.date.issued2020
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14077
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14077
dc.description.abstractReconstructing surfaces from scanned 3D points has been an important research area for several decades. One common approach that has proven efficient and robust to noise is implicit surface reconstruction, i.e. fitting to the points a 3D scalar function (such as an indicator function or signed-distance field) and then extracting an isosurface. Though many techniques fall within this category, existing methods either impose no boundary constraints or impose Dirichlet/Neumann conditions on the surface of a bounding box containing the scanned data. In this work, we demonstrate the benefit of supporting Dirichlet constraints on a general boundary. To this end, we adapt the Screened Poisson Reconstruction algorithm to input a constraint envelope in addition to the oriented point cloud. We impose Dirichlet boundary conditions, forcing the reconstructed implicit function to be zero outside this constraint surface. Using a visual hull and/or depth hull derived from RGB-D scans to define the constraint envelope, we obtain substantially improved surface reconstructions in regions of missing data.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectI.3.5 [Computer Graphics]
dc.subjectComputational Geometry and Object Modeling
dc.subjectGeometric algorithms
dc.subjectlanguages
dc.subjectand systems
dc.titlePoisson Surface Reconstruction with Envelope Constraintsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersSurface Reconstruction
dc.description.volume39
dc.description.number5
dc.identifier.doi10.1111/cgf.14077
dc.identifier.pages173-182


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  • 39-Issue 5
    Geometry Processing 2020 - Symposium Proceedings

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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License