Weak Convex Decomposition by Lines-of-sight

Simple item page
dc.contributor.authorAsafi, Shmuelen_US
dc.contributor.authorGoren, Avien_US
dc.contributor.authorCohen-Or, Danielen_US
dc.contributor.editorYaron Lipman and Hao Zhangen_US
dc.date.accessioned2015-02-28T15:50:29Z
dc.date.available2015-02-28T15:50:29Z
dc.date.issued2013en_US
dc.description.abstractWe define the convexity rank of a set of points to be the portion of mutually visible pairs of points out of the total number of pairs. Based on this definition of weak convexity, we introduce a spectral method that decomposes a given shape into weakly convex regions. The decomposition is applied without explicitly measuring the convexity rank. The method merely amounts to a spectral clustering of a matrix representing the all-pairs line of sight. Our method can be directly applied on an oriented point cloud and does not require any topological information, nor explicit concavity or convexity measures. We demonstrate the efficiency of our algorithm on a large number of examples and compare them qualitatively with competitive approaches.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.identifier.doi10.1111/cgf.12169en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12169en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleWeak Convex Decomposition by Lines-of-sighten_US
Files
Collections
32-Issue 5
SGP13: Eurographics Symposium on Geometry Processing (CGF 32-5)