Visualization of Uncertain Multivariate Data via Feature Confidence Level-Sets
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Recent 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.
Description
@inproceedings{10.2312:evs.20211053,
booktitle = {EuroVis 2021 - Short Papers},
editor = {Agus, Marco and Garth, Christoph and Kerren, Andreas},
title = {{Visualization of Uncertain Multivariate Data via Feature Confidence Level-Sets}},
author = {Sane, Sudhanshu and Athawale, Tushar M. and Johnson, Chris R.},
year = {2021},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-143-4},
DOI = {10.2312/evs.20211053}
}