K
Kristin Potter
Researcher at University of Utah
Publications - 31
Citations - 1483
Kristin Potter is an academic researcher from University of Utah. The author has contributed to research in topics: Visualization & Data visualization. The author has an hindex of 15, co-authored 31 publications receiving 1280 citations. Previous affiliations of Kristin Potter include Scientific Computing and Imaging Institute & University of Oregon.
Papers
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Journal ArticleDOI
Resolution independent NPR-style 3D line textures
Kristin Potter,Amy A. Gooch,Bruce Gooch,Peter Willemsen,Joe Kniss,Richard F. Riesenfeld,Peter Shirley +6 more
TL;DR: A clipping algorithm is presented to enable 3D lines to reside only in the interior of the 3D model without exposing the underlying triangulated mesh, and the resulting system produces interactive illustrations with high visual quality that are free from animation artifacts.
A Flexible Approach for the Statistical Visualization of Ensemble Data.
TL;DR: It is argued that combining multiple linked statistical displays yields a clearer presentation of the data and facilitates a greater level of visual data analysis in contrast to methods that present large amounts of diverse information in a single display.
Proceedings Article
Uncertainty visualization in forward and inverse cardiac models
Brett M. Burton,Burak Erem,Kristin Potter,Paul Rosen,Chris R. Johnson,Dana H. Brooks,Rob S. MacLeod +6 more
TL;DR: Through dimensionality reduction and superimposed mean and standard deviation measures over time, this work was able to display key features in large ensembles of data and highlight regions of interest where larger uncertainties exist.
The visualization of uncertainty
TL;DR: This dissertation seeks to advance approaches for uncertainty visualization by exploring techniques from scientific and information visualization, creating new visual devices to handle the complexities of uncertainty data, and combining the most effective display methods into the Ensemble-Vis framework for visual data analysis.
Journal ArticleDOI
Occam's razor and petascale visual data analysis
E.W. Bethel,Chris R. Johnson,Sean Ahern,John B. Bell,Peer-Timo Bremer,Hank Childs,Estelle Cormier-Michel,Marcus S. Day,Eduard Deines,Thomas Fogal,Christoph Garth,Cameron Geddes,Hans Hagen,Bernd Hamann,Charles Hansen,Janet Jacobsen,Kenneth I. Joy,Jens Krüger,Jeremy S. Meredith,Peter Messmer,George Ostrouchov,Valerio Pascucci,Kristin Potter,Prabhat,Dave Pugmire,Oliver Rubel,Allen Sanderson,Cláudio T. Silva,Daniela Ushizima,Gunther H. Weber,Brad Whitlock,Kesheng Wu +31 more
TL;DR: An effective approach will likely combine application architectures that are capable of running on today's largest platforms to address the challenges posed by large data with visual data analysis techniques that help find, represent, and effectively convey scientifically interesting features and phenomena.