Accurate Synthesis of Multi-Class Disk Distributions

dc.contributor.authorEcormier-Nocca, Pierreen_US
dc.contributor.authorMemari, Pooranen_US
dc.contributor.authorGain, Jamesen_US
dc.contributor.authorCani, Marie-Pauleen_US
dc.contributor.editorAlliez, Pierre and Pellacini, Fabioen_US
dc.date.accessioned2019-05-05T17:39:38Z
dc.date.available2019-05-05T17:39:38Z
dc.date.issued2019
dc.description.abstractWhile analysing and synthesising 2D distributions of points has been applied both to the generation of textures with discrete elements and for populating virtual worlds with 3D objects, the results are often inaccurate since the spatial extent of objects cannot be expressed.We introduce three improvements enabling the synthesis of more general distributions of elements. First, we extend continuous pair correlation function (PCF) algorithms to multi-class distributions using a dependency graph, thereby capturing interrelationships between distinct categories of objects. Second, we introduce a new normalised metric for disks, which makes the method applicable to both point and possibly overlapping disk distributions. The metric is specifically designed to distinguish perceptually salient features, such as disjoint, tangent, overlapping, or nested disks. Finally, we pay particular attention to convergence of the mean PCF as well as the validity of individual PCFs, by taking into consideration the variance of the input. Our results demonstrate that this framework can capture and reproduce real-life distributions of elements representing a variety of complex semi-structured patterns, from the interaction between trees and the understorey in a forest to droplets of water. More generally, it applies to any category of 2D object whose shape is better represented by bounding circles than points.en_US
dc.description.number2
dc.description.sectionheadersSampling
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume38
dc.identifier.doi10.1111/cgf.13627
dc.identifier.issn1467-8659
dc.identifier.pages157-168
dc.identifier.urihttps://doi.org/10.1111/cgf.13627
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13627
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectTheory of computation
dc.subjectRandomness
dc.subjectgeometry and discrete structures
dc.subjectComputing methodologies
dc.subjectShape modeling
dc.titleAccurate Synthesis of Multi-Class Disk Distributionsen_US
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