Visual Reconstructability as a Quality Metric for Flow Visualization

dc.contributor.authorJänicke, Heikeen_US
dc.contributor.authorWeidner, Thomasen_US
dc.contributor.authorChung, Daviden_US
dc.contributor.authorLaramee, Robert S.en_US
dc.contributor.authorTownsend, Peteren_US
dc.contributor.authorChen, Minen_US
dc.contributor.editorH. Hauser, H. Pfister, and J. J. van Wijken_US
dc.date.accessioned2014-02-21T20:23:27Z
dc.date.available2014-02-21T20:23:27Z
dc.date.issued2011en_US
dc.description.abstractWe present a novel approach for the evaluation of 2D flow visualizations based on the visual reconstructability of the input vector fields. According to this metric, a visualization has high quality if the underlying data can be reliably reconstructed from the image. This approach provides visualization creators with a cost-effective means to assess the quality of visualization results objectively. We present a vision-based reconstruction system for the three most commonly-used visual representations of vector fields, namely streamlines, arrow glyphs, and line integral convolution. To demonstrate the use of visual reconstructability as a quality metric, we consider a selection of vector fields obtained from numerical simulations, containing typical flow features. We apply the three types of visualization to each dataset, and compare the visualization results based on their visual reconstructability of the original vector field.en_US
dc.description.number3en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume30en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2011.01927.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleVisual Reconstructability as a Quality Metric for Flow Visualizationen_US
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