Visual coherence for large-scale line-plot visualizations

  • Authors:

  • Philipp Muigg;Markus Hadwiger;Helmut Doleisch;Eduard Gröller

  • Affiliations:

  • Vienna University of Technology and SimVis GmbH, Vienna, Austria;King Abdullah University of Science and Technology, Saudi Arabia;SimVis GmbH, Vienna, Austria;Vienna University of Technology, Austria

  • Venue:
  • EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
  • Year:
  • 2011

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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.