A Hierarchical Approach for Regular Centroidal Voronoi Tessellations

dc.contributor.authorWang, L.en_US
dc.contributor.authorHétroy‐Wheeler, F.en_US
dc.contributor.authorBoyer, E.en_US
dc.contributor.editorChen, Min and Zhang, Hao (Richard)en_US
dc.date.accessioned2016-03-01T14:13:09Z
dc.date.available2016-03-01T14:13:09Z
dc.date.issued2016en_US
dc.description.abstractIn this paper, we consider Centroidal Voronoi Tessellations (CVTs) and study their regularity. CVTs are geometric structures that enable regular tessellations of geometric objects and are widely used in shape modelling and analysis. While several efficient iterative schemes, with defined local convergence properties, have been proposed to compute CVTs, little attention has been paid to the evaluation of the resulting cell decompositions. In this paper, we propose a regularity criterion that allows us to evaluate and compare CVTs independently of their sizes and of their cell numbers. This criterion allows us to compare CVTs on a common basis. It builds on earlier theoretical work showing that second moments of cells converge to a lower bound when optimizing CVTs. In addition to proposing a regularity criterion, this paper also considers computational strategies to determine regular CVTs. We introduce a hierarchical framework that propagates regularity over decomposition levels and hence provides CVTs with provably better regularities than existing methods. We illustrate these principles with a wide range of experiments on synthetic and real models.In this paper, we consider Centroidal Voronoi Tessellations (CVTs) and study their regularity. CVTs are geometric structures that enable regular tessellations of geometric objects and are widely used in shape modelling and analysis.While several efficient iterative schemes, with defined local convergence properties, have been proposed to compute CVTs, little attention has been paid to the evaluation of the resulting cell decompositions. In this paper, we propose a regularity criterion that allows us to evaluate and compare CVTs independently of their sizes and of their cell numbers.en_US
dc.description.number1en_US
dc.description.sectionheadersArticlesen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume35en_US
dc.identifier.doi10.1111/cgf.12716en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12716en_US
dc.publisherCopyright © 2016 The Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectcategoriesen_US
dc.subjectsubject descriptorsen_US
dc.subjectComputer Graphics [I.3.5]: Computational Geometry and Object Modelling—Curveen_US
dc.subjectsurfaceen_US
dc.subjectsolid and object representations; I.5.3 [Pattern Recognition]: Clustering—en_US
dc.titleA Hierarchical Approach for Regular Centroidal Voronoi Tessellationsen_US
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