Visual coherence for large-scale line-plot visualizations

Philipp Muigg, Markus Hadwiger, Helmut Doleisch, Eduard M. Gröller

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

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).
Original languageEnglish (US)
Pages (from-to)643-652
Number of pages10
JournalComputer Graphics Forum
Volume30
Issue number3
DOIs
StatePublished - Jun 28 2011

ASJC Scopus subject areas

  • Computer Networks and Communications

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