Similarity-Based Surface Modelling Using Geodesic Fans

dc.contributor.authorZelinka, Steveen_US
dc.contributor.authorGarland, Michaelen_US
dc.contributor.editorRoberto Scopigno and Denis Zorinen_US
dc.date.accessioned2014-01-29T09:19:54Z
dc.date.available2014-01-29T09:19:54Z
dc.date.issued2004en_US
dc.description.abstractWe present several powerful new techniques for similarity-based modelling of surfaces using geodesic fans, a new framework for local surface comparison. Similarity-based surface modelling provides intelligent surface manipulation by simultaneously applying a modification to all similar areas of the surface. We demonstrate similaritybased painting, deformation, and filtering of surfaces, and show how to vary our similarity measure to encompass geometry, textures, or other arbitrary signals. Geodesic fans are neighbourhoods uniformly sampled in the geodesic polar coordinates of a point on a surface. We show how geodesic fans offer fast approximate alignment and comparison of surface neighbourhoods using simple spoke reordering. As geodesic fans offer a a structurally equivalent definition of neighbourhoods everywhere on a surface, they are amenable to standard acceleration techniques and are well-suited to extending image domain methods for modelling by example to surfaces.en_US
dc.description.seriesinformationSymposium on Geometry Processingen_US
dc.identifier.isbn3-905673-13-4en_US
dc.identifier.issn1727-8384en_US
dc.identifier.urihttp://dx.doi.org/10.2312/SGP/SGP04/209-218en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Curve, surface, solid, and object representations I.4.7 [Image Processing and Computer Vision]: Size and shapeen_US
dc.titleSimilarity-Based Surface Modelling Using Geodesic Fansen_US
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