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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.date.accessioned2019-06-02T18:27:57Z
dc.date.available2019-06-02T18:27:57Z
dc.date.issued2019
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.13692
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13692
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.subjectHuman
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
dc.description.volume38
dc.description.number3
dc.identifier.doi10.1111/cgf.13692
dc.identifier.pages325-336


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  • 38-Issue 3
    EuroVis 2019 - Conference Proceedings

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