Visualization of Uncertain Multivariate Data via Feature Confidence Level-Sets

dc.contributor.authorSane, Sudhanshuen_US
dc.contributor.authorAthawale, Tushar M.en_US
dc.contributor.authorJohnson, Chris R.en_US
dc.contributor.editorAgus, Marco and Garth, Christoph and Kerren, Andreasen_US
dc.date.accessioned2021-06-12T11:03:24Z
dc.date.available2021-06-12T11:03:24Z
dc.date.issued2021
dc.description.abstractRecent advancements in multivariate data visualization have opened new research opportunities for the visualization community. In this paper, we propose an uncertain multivariate data visualization technique called feature confidence level-sets. Conceptually, feature level-sets refer to level-sets of multivariate data. Our proposed technique extends the existing idea of univariate confidence isosurfaces to multivariate feature level-sets. Feature confidence level-sets are computed by considering the trait for a specific feature, a confidence interval, and the distribution of data at each grid point in the domain. Using uncertain multivariate data sets, we demonstrate the utility of the technique to visualize regions with uncertainty in relation to the specific trait or feature, and the ability of the technique to provide secondary feature structure visualization based on uncertainty.en_US
dc.description.sectionheadersScientific Visualization
dc.description.seriesinformationEuroVis 2021 - Short Papers
dc.identifier.doi10.2312/evs.20211053
dc.identifier.isbn978-3-03868-143-4
dc.identifier.pages43-47
dc.identifier.urihttps://doi.org/10.2312/evs.20211053
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evs20211053
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectScientific visualization
dc.titleVisualization of Uncertain Multivariate Data via Feature Confidence Level-Setsen_US
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