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2015 IEEE Conference on Visual Analytics Science and Technology (VAST) (2015)
Chicago, IL, USA
Oct. 25, 2015 to Oct. 30, 2015
ISBN: 978-1-4673-9783-4
pp: 211-212
Khairi Reda , Argonne National Laboratory, USA
Alberto Gonzalez , University of Hawai'i at M?noa, USA
Jason Leigh , University of Hawai'i at M?noa, USA
Michael E. Papka , Argonne National Laboratory, USA
ABSTRACT
Visualization helps users infer structures and relationships in the data by encoding information as visual features that can be processed by the human visual-perceptual system. However, users would typically need to expend significant effort to scan and analyze a large number of views before they can begin to recognize relationships in a visualization. We propose a technique to partially automate the process of analyzing visualizations. By deriving and analyzing image-space features from visualizations, we can detect perceptually-separable patterns in the information space. We summarize these patterns with a tree-based meta-visualization and present it to the user to aid exploration. We illustrate this technique with an example scenario involving the analysis of census data.
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CITATION

K. Reda, A. Gonzalez, J. Leigh and M. E. Papka, "Tell me what do you see: Detecting perceptually-separable visual patterns via clustering of image-space features in visualizations," 2015 IEEE Conference on Visual Analytics Science and Technology (VAST), Chicago, IL, USA, 2015, pp. 211-212.
doi:10.1109/VAST.2015.7347683
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