3D Shape Matching based on Geodesic Distance Distributions

dc.contributor.authorMartinek, Michaelen_US
dc.contributor.authorFerstl, Matthiasen_US
dc.contributor.authorGrosso, Robertoen_US
dc.contributor.editorMichael Goesele and Thorsten Grosch and Holger Theisel and Klaus Toennies and Bernhard Preimen_US
dc.date.accessioned2013-11-08T10:35:42Z
dc.date.available2013-11-08T10:35:42Z
dc.date.issued2012en_US
dc.description.abstractIn this work, we present a signature for 3D shapes which is based on the distribution of geodesic distances. Our shape descriptor is invariant with respect to rotation and scaling as well as articulations of the object. It consists of shape histograms which reflect the geodesic distance distribution of randomly chosen pairs of surface points as well as the distribution of geodesic eccentricity and centricity. We show, that a combination of these shape histograms provides good discriminative power to find similar objects in 3D databases even if they are differently articulated. In order to improve the efficiency of the feature extraction, we employ a fast voxelization method and compute the geodesic distances on a boundary voxel representation of the objects.en_US
dc.description.seriesinformationVision, Modeling and Visualizationen_US
dc.identifier.isbn978-3-905673-95-1en_US
dc.identifier.urihttps://doi.org/10.2312/PE/VMV/VMV12/219-220en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.5.3 [Computer Graphics]en_US
dc.subjectComputational Geometry and Object Modelingen_US
dc.subjectGeometric algorithmsen_US
dc.subjectlanguagesen_US
dc.subjectand systemsen_US
dc.title3D Shape Matching based on Geodesic Distance Distributionsen_US
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