Visual coherence for large-scale line-plot visualizations

Handle URI:
http://hdl.handle.net/10754/561794
Title:
Visual coherence for large-scale line-plot visualizations
Authors:
Muigg, Philipp; Hadwiger, Markus ( 0000-0003-1239-4871 ) ; Doleisch, Helmut; Gröller, Eduard M.
Abstract:
Displaying 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. © 2011 The Author(s).
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer Science Program; Visual Computing Center (VCC)
Publisher:
Wiley-Blackwell
Journal:
Computer Graphics Forum
Issue Date:
Jun-2011
DOI:
10.1111/j.1467-8659.2011.01913.x
Type:
Article
ISSN:
01677055
Sponsors:
The authors thank Thomas Schultz and Andrea Kratz for valuable input on tensor-related topics, and Wolfgang Freiler for help with figures. The diesel particulate filter data set is courtesy of AVL List GmbH, Graz, Austria. Parts of this work were funded by the Austrian Research Funding Agency (FFG) in the scope of the project "AutARG" ( No. 819352)
Appears in Collections:
Articles; Computer Science Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorMuigg, Philippen
dc.contributor.authorHadwiger, Markusen
dc.contributor.authorDoleisch, Helmuten
dc.contributor.authorGröller, Eduard M.en
dc.date.accessioned2015-08-03T09:04:46Zen
dc.date.available2015-08-03T09:04:46Zen
dc.date.issued2011-06en
dc.identifier.issn01677055en
dc.identifier.doi10.1111/j.1467-8659.2011.01913.xen
dc.identifier.urihttp://hdl.handle.net/10754/561794en
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. © 2011 The Author(s).en
dc.description.sponsorshipThe authors thank Thomas Schultz and Andrea Kratz for valuable input on tensor-related topics, and Wolfgang Freiler for help with figures. The diesel particulate filter data set is courtesy of AVL List GmbH, Graz, Austria. Parts of this work were funded by the Austrian Research Funding Agency (FFG) in the scope of the project "AutARG" ( No. 819352)en
dc.publisherWiley-Blackwellen
dc.titleVisual coherence for large-scale line-plot visualizationsen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentComputer Science Programen
dc.contributor.departmentVisual Computing Center (VCC)en
dc.identifier.journalComputer Graphics Forumen
dc.contributor.institutionVienna University of Technology, Austriaen
dc.contributor.institutionSimVis GmbH, Vienna, Austriaen
kaust.authorHadwiger, Markusen
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