Sifted Disks

dc.contributor.authorEbeida, Mohamed S.en_US
dc.contributor.authorMahmoud, Ahmed H.en_US
dc.contributor.authorAwad, Muhammad A.en_US
dc.contributor.authorMohammed, Mohammed A.en_US
dc.contributor.authorMitchell, Scott A.en_US
dc.contributor.authorRand, Alexanderen_US
dc.contributor.authorOwens, John D.en_US
dc.contributor.editorI. Navazo, P. Poulinen_US
dc.date.accessioned2015-02-28T15:27:04Z
dc.date.available2015-02-28T15:27:04Z
dc.date.issued2013en_US
dc.description.abstractWe introduce the Sifted Disk technique for locally resampling a point cloud in order to reduce the number of points. Two neighboring points are removed and we attempt to find a single random point that is sufficient to replace them both. The resampling respects the original sizing function; In that sense it is not a coarsening. The angle and edge length guarantees of a Delaunay triangulation of the points are preserved. The sifted point cloud is still suitable for texture synthesis because the Fourier spectrum is largely unchanged. We provide an efficient algorithm, and demonstrate that sifting uniform Maximal Poisson-disk Sampling (MPS) and Delaunay Refinement (DR) points reduces the number of points by about 25 percent, and achieves a density about 1/3 more than the theoretical minimum. We show two-dimensional stippling and meshing applications to demonstrate the significance of the concept.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12071en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subjectI.3.5 [Computing Methodologies]en_US
dc.subjectComputer Graphicsen_US
dc.subjectComputational Geometry and Object Modelingen_US
dc.titleSifted Disksen_US
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