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dc.contributor.authorIglesias, Jose A.en_US
dc.contributor.authorBerkels, Benjaminen_US
dc.contributor.authorRumpf, Martinen_US
dc.contributor.authorScherzer, Otmaren_US
dc.contributor.editorMichael Bronstein and Jean Favre and Kai Hormannen_US
dc.date.accessioned2014-02-01T16:26:04Z
dc.date.available2014-02-01T16:26:04Z
dc.date.issued2013en_US
dc.identifier.isbn978-3-905674-51-4en_US
dc.identifier.urihttp://dx.doi.org/10.2312/PE.VMV.VMV13.089-096en_US
dc.description.abstractFrequently, one aims at the co-registration of geometries described implicitly by images as level sets. This paper proposes a novel shape sensitive approach for the matching of such implicit surfaces. Motivated by physical models of elastic shells a variational approach is proposed, which distinguishes two different types of energy contributions: a membrane energy measuring the rate of tangential distortion when deforming the reference surface into the template surface, and a bending energy reflecting the required amount of bending. The variational model is formulated via a narrow band approach. The built in tangential distortion energy leads to a suitable equidistribution of deformed length and area elements, under the optimal matching deformation, whereas the minimization of the bending energy fosters a proper matching of shape features such as crests, valleys or bumps. In the implementation, a spatial discretization via finite elements, a nonlinear conjugate gradient scheme with a Sobolev metric, and a cascadic multilevel optimization strategy are used. The features of the proposed method are discussed via applications both for synthetic and realistic examples.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.5 [Computer Graphics]en_US
dc.subjectComputational Geometry and Object Modelingen_US
dc.subjectBoundary representationsen_US
dc.subjectI.4.3 [Image Processing and Computer Vision]en_US
dc.subjectEnhancementen_US
dc.subjectRegistrationen_US
dc.titleA Thin Shell Approach to the Registration of Implicit Surfacesen_US
dc.description.seriesinformationVision, Modeling & Visualizationen_US


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  • VMV13
    ISBN 978-3-905674-51-4

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