Parallel Construction of k-Nearest Neighbor Graphs for Point Clouds

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dc.contributor.authorConnor, M.en_US
dc.contributor.authorKumar, P.en_US
dc.contributor.editorHans-Christian Hege and David Laidlaw and Renato Pajarola and Oliver Staadten_US
dc.date.accessioned2014-01-29T17:14:32Z
dc.date.available2014-01-29T17:14:32Z
dc.date.issued2008en_US
dc.description.abstractWe present a parallel algorithm for k-nearest neighbor graph construction that uses Morton ordering. Experiments show that our approach has the following advantages over existing methods: (1) Faster construction of k-nearest neighbor graphs in practice on multi-core machines. (2) Less space usage. (3) Better cache efficiency. (4) Ability to handle large data sets. (5) Ease of parallelization and implementation.en_US
dc.description.seriesinformationIEEE/ EG Symposium on Volume and Point-Based Graphicsen_US
dc.identifier.isbn978-3-905674-12-5en_US
dc.identifier.issn1727-8376en_US
dc.identifier.urihttps://doi.org/10.2312/VG/VG-PBG08/025-031en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: k-NN Graphsen_US
dc.titleParallel Construction of k-Nearest Neighbor Graphs for Point Cloudsen_US
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VG-PBG08: Eurographics/IEEE VGTC on Volume and Point-Based Graphics
VG-PBG08: Eurographics/IEEE VGTC on Volume and Point-Based Graphics