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dc.contributor.authorBrüel-Gabrielsson, Rickarden_US
dc.contributor.authorGanapathi-Subramanian, Vigneshen_US
dc.contributor.authorSkraba, Primozen_US
dc.contributor.authorGuibas, Leonidas J.en_US
dc.contributor.editorJacobson, Alec and Huang, Qixingen_US
dc.description.abstractWe present an approach to incorporate topological priors in the reconstruction of a surface from a point scan. We base the reconstruction on basis functions which are optimized to provide a good fit to the point scan while satisfying predefined topological constraints. We optimize the parameters of a model to obtain a likelihood function over the reconstruction domain. The topological constraints are captured by persistence diagrams which are incorporated within the optimization algorithm to promote the correct topology. The result is a novel topology-aware technique which can (i) weed out topological noise from point scans, and (ii) capture certain nuanced properties of the underlying shape which could otherwise be lost while performing surface reconstruction. We show results reconstructing shapes with multiple potential topologies, compare to other classical surface construction techniques, and show the completion of real scan data.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.subjectTheory of computation
dc.subjectComputational geometry
dc.subjectComputing methodologies
dc.subjectShape modeling
dc.subjectMathematics of computing
dc.subjectAlgebraic topology
dc.titleTopology-Aware Surface Reconstruction for Point Cloudsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersSurface Reconstruction

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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