Show simple item record

dc.contributor.authorJänicke, Heikeen_US
dc.contributor.authorChen, Minen_US
dc.contributor.editorG. Melancon, T. Munzner, and D. Weiskopfen_US
dc.date.accessioned2014-02-21T20:06:23Z
dc.date.available2014-02-21T20:06:23Z
dc.date.issued2010en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/j.1467-8659.2009.01667.xen_US
dc.description.abstractSalience detection is a principle mechanism to facilitate visual attention. A good visualization guides the observer s attention to the relevant aspects of the representation. Hence, the distribution of salience over a visualization image is an essential measure of the quality of the visualization. We describe a method for computing such a metric for a visualization image in the context of a given dataset. We show how this technique can be used to analyze a visualization s salience, improve an existing visualization, and choose the best representation from a set of alternatives. The usefulness of this proposed metric is illustrated using examples from information visualization, volume visualization and flow visualization.en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleA Salience-based Quality Metric for Visualizationen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume29en_US
dc.description.number3en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record