Visual Coherence for Large-Scale Line-Plot Visualizations

dc.contributor.authorMuigg, Philippen_US
dc.contributor.authorHadwiger, Markusen_US
dc.contributor.authorDoleisch, Helmuten_US
dc.contributor.authorGröller, Eduarden_US
dc.contributor.editorH. Hauser, H. Pfister, and J. J. van Wijken_US
dc.date.accessioned2014-02-21T20:23:18Z
dc.date.available2014-02-21T20:23:18Z
dc.date.issued2011en_US
dc.description.abstractDisplaying a large number of lines within a limited amount of screen space is a task that is common to many different classes of visualization techniques such as time-series visualizations, parallel coordinates, link-node diagrams, and phase-space diagrams. This paper addresses the challenging problems of cluttering and overdraw inherent to such visualizations. We generate a 2x2 tensor field during line rasterization that encodes the distribution of line orientations through each image pixel. Anisotropic diffusion of a noise texture is then used to generate a dense, coherent visualization of line orientation. In order to represent features of different scales, we employ a multi-resolution representation of the tensor field. The resulting technique can easily be applied to a wide variety of line-based visualizations. We demonstrate this for parallel coordinates, a time-series visualization, and a phase-space diagram. Furthermore, we demonstrate how to integrate a focus+context approach by incorporating a second tensor field. Our approach achieves interactive rendering performance for large data sets containing millions of data items, due to its image-based nature and ease of implementation on GPUs. Simulation results from computational fluid dynamics are used to evaluate the performance and usefulness of the proposed method.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.1467-8659.2011.01913.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleVisual Coherence for Large-Scale Line-Plot Visualizationsen_US
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