General Point Sampling with Adaptive Density and Correlations

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dc.contributor.authorRoveri, Riccardoen_US
dc.contributor.authorÖztireli, A. Cengizen_US
dc.contributor.authorGross, Markusen_US
dc.contributor.editorLoic Barthe and Bedrich Benesen_US
dc.date.accessioned2017-04-22T16:25:51Z
dc.date.available2017-04-22T16:25:51Z
dc.date.issued2017
dc.description.abstractAnalyzing and generating sampling patterns are fundamental problems for many applications in computer graphics. Ideally, point patterns should conform to the problem at hand with spatially adaptive density and correlations. Although there exist excellent algorithms that can generate point distributions with spatially adaptive density or anisotropy, the pair-wise correlation model, blue noise being the most common, is assumed to be constant throughout the space. Analogously, by relying on possibly modulated pair-wise difference vectors, the analysis methods are designed to study only such spatially constant correlations. In this paper, we present the first techniques to analyze and synthesize point patterns with adaptive density and correlations. This provides a comprehensive framework for understanding and utilizing general point sampling. Starting from fundamental measures from stochastic point processes, we propose an analysis framework for general distributions, and a novel synthesis algorithm that can generate point distributions with spatio-temporally adaptive density and correlations based on a locally stationary point process model. Our techniques also extend to general metric spaces. We illustrate the utility of the new techniques on the analysis and synthesis of real-world distributions, image reconstruction, spatio-temporal stippling, and geometry sampling.en_US
dc.description.number2
dc.description.sectionheadersSample, Paint, and Visualize
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume36
dc.identifier.doi10.1111/cgf.13111
dc.identifier.issn1467-8659
dc.identifier.pages107-117
dc.identifier.urihttps://doi.org/10.1111/cgf.13111
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13111
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.3 [Computer Graphics]
dc.subjectPicture/Image Generation
dc.subjectAntialiasing
dc.subjectI.3.7 [Computer Graphics]
dc.subjectThree Dimensional Graphics and Realism
dc.subjectColor
dc.subjectshading
dc.subjectshadowing
dc.subjectand texture
dc.subjectI.3.5 [Computer Graphics]
dc.subjectComputational Geometry and Object Modeling
dc.subjectCurve
dc.subjectsurface
dc.subjectsolid
dc.subjectand object representations
dc.subjectI.4.1 [Image Processing and Computer Vision]
dc.subjectDigitization and Image Capture
dc.subjectSampling
dc.titleGeneral Point Sampling with Adaptive Density and Correlationsen_US
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