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dc.contributor.authorGerrits, Timen_US
dc.contributor.authorRössl, Christianen_US
dc.contributor.authorTheisel, Holgeren_US
dc.contributor.editorGleicher, Michael and Viola, Ivan and Leitte, Heikeen_US
dc.description.abstractMeasured data often incorporates some amount of uncertainty, which is generally modeled as a distribution of possible samples. In this paper, we consider second-order symmetric tensors with uncertainty. In the 3D case, this means the tensor data consists of 6 coefficients - uncertainty, however, is encoded by 21 coefficients assuming a multivariate Gaussian distribution as model. The high dimension makes the direct visualization of tensor data with uncertainty a difficult problem, which was until now unsolved. The contribution of this paper consists in the design of glyphs for uncertain second-order symmetric tensors in 2D and 3D. The construction consists of a standard glyph for the mean tensor that is augmented by a scalar field that represents uncertainty. We show that this scalar field and therefore the displayed glyph encode the uncertainty comprehensively, i.e., there exists a bijective map between the glyph and the parameters of the distribution. Our approach can extend several classes of existing glyphs for symmetric tensors to additionally encode uncertainty and therefore provides a possible foundation for further uncertain tensor glyph design. For demonstration, we choose the well-known superquadric glyphs, and we show that the uncertainty visualization satisfies all their design constraints.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectcentered computing
dc.subjectScientific visualization
dc.titleTowards Glyphs for Uncertain Symmetric Second-Order Tensorsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersHigher-Order Data Types

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  • 38-Issue 3
    EuroVis 2019 - Conference Proceedings

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