Shape Segmentation and Matching from Noisy Point Clouds

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dc.contributor.authorDey, Tamal K.en_US
dc.contributor.authorGiesen, Joachimen_US
dc.contributor.authorGoswami, Samraten_US
dc.contributor.editorMarkus Gross and Hanspeter Pfister and Marc Alexa and Szymon Rusinkiewiczen_US
dc.date.accessioned2014-01-29T16:25:48Z
dc.date.available2014-01-29T16:25:48Z
dc.date.issued2004en_US
dc.description.abstractWe present the implementation results of a shape segmentation technique and an associated shape matching method whose input is a point sample from the shape. The sample is allowed to be noisy in the sense that they may scatter around the boundary of the shape instead of lying exactly on it. The algorithm is simple and mostly combinatorial in that it builds a single data structure, the Delaunay triangulation of the point set, and groups the tetrahedra to form the segments. A small set of weighted points are derived from the segments which are used as signatures to match shapes. Experimental results establish the effectiveness of the method in practice.en_US
dc.description.seriesinformationSPBG'04 Symposium on Point - Based Graphics 2004en_US
dc.identifier.isbn3-905673-09-6en_US
dc.identifier.issn1811-7813en_US
dc.identifier.urihttps://doi.org/10.2312/SPBG/SPBG04/193-199en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Modeling3D Shape Matching, Point-Based Graphics.en_US
dc.titleShape Segmentation and Matching from Noisy Point Cloudsen_US
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