August 2016
Volume 16, Issue 12
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2016
Applying Impressionist Painterly Techniques to Data Visualization
Author Affiliations
  • Pavel Kozik
    1Department of Psychology, University of British Columbia, Vancouver, Canada
  • Laura Tateosian
    2Department of Computer Science, North Carolina State University, Raleigh, United States
  • Christopher Healey
    2Department of Computer Science, North Carolina State University, Raleigh, United States
  • James Enns
    1Department of Psychology, University of British Columbia, Vancouver, Canada
Journal of Vision September 2016, Vol.16, 188. doi:10.1167/16.12.188
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      Pavel Kozik, Laura Tateosian, Christopher Healey, James Enns; Applying Impressionist Painterly Techniques to Data Visualization . Journal of Vision 2016;16(12):188. doi: 10.1167/16.12.188.

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      © 2017 Association for Research in Vision and Ophthalmology.

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Abstract

An important task of science is to communicate complex data to peers and the public. Here we ask whether harnessing the painterly techniques of impressionist-era painters is beneficial. In two experiments, participants viewed weather maps from the International Panel of Climate Change that were rendered using either an industry-standard technique (glyphs) or one of three styles inspired from impressionist masters. The glyph technique used rectangular glyphs that vary properties of color and texture (e.g. hue, saturation and size) to represent corresponding data values. For the impressionist styles, regions of maximum contrast in the underlying data were rendered using brushstroke algorithms to emphasize interpretational complexity (two distinct layers of paint where unique regions have greater brushstroke overlap), indication and detail (unique regions are rendered with increased brushstroke thickness and density), and visual complexity (unique regions are rendered with different brushstrokes at a global level and reinforced with increased brushstroke variation at a local level). Visual complexity was expected to be more memorable and allow for more accurate information extraction because it both draws attention to distinct image regions and engages the viewer at those locations with increased brushstroke variability. In Experiment 1 thirty participants completed a new–old recognition test for which d-prime values of visual complexity and glyph were comparable, and both superior to the other styles. Experiment 2 tested the accuracy of numerosity estimation with a different group of thirty participants and here visual complexity was superior above all other styles. An exit poll completed at the end of both studies further revealed that the style participants identified as being "most liked" associated with higher performance relative those not selected. Incidental eye-tracking revealed impressionist styles elicited greater visual exploration over glyphs. These results offer a proof-of-concept that visualizations based on Impressionist brushstrokes can be memorable, functional, and engaging.

Meeting abstract presented at VSS 2016

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