A Hierarchical Approach for Regular Centroidal Voronoi Tessellations. (28th September 2015)

• Record Type: Journal Article
• Authors: Wang, L.; Hétroy‐Wheeler, F.; Boyer, E.
• Is Part Of: Computer graphics forum. Volume 35:Number 1(2016)
• Page Start: 152
• Page End: 165
• Publication Date: 2015-09-28
• Subjects: categories -- subject descriptors -- Computer Graphics [I.3.5]: Computational Geometry and Object Modelling—Curve -- surface -- solid and object representations; I.5.3 [Pattern Recognition]: Clustering—; Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.12716
• Languages: English
• ISSNs: 0167-7055

Abstract

Abstract : 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. Abstract : 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. 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.