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Topology-Based Flow Visualization, The State of the Art

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Topology-based Methods in Visualization

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Summary

Flow visualization research has made rapid advances in recent years, especially in the area of topology-based flow visualization. The ever increasing size of scientific data sets favors algorithms that are capable of extracting important subsets of the data, leaving the scientist with a more manageable representation that may be visualized interactively. Extracting the topology of a flow achieves the goal of obtaining a compact representation of a vector or tensor field while simultaneously retaining its most important features. We present the state of the art in topology-based flow visualization techniques. We outline numerous topology-based algorithms categorized according to the type and dimensionality of data on which they operate and according to the goal-oriented nature of each method. Topology tracking algorithms are also discussed. The result serves as a useful introduction and overview to research literature concerned with the study of topology-based flow visualization.

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Authors and Affiliations

  1. Department of Computer Science, Swansea University, UK

    Robert S. Laramee

  2. VRVis Research Center, Vienna, Austria

    Helwig Hauser

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  1. Robert S. Laramee
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  2. Helwig Hauser
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  3. Lingxiao Zhao
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  4. Frits H. Post
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Editors and Affiliations

  1. Department of Informatics, University of Bergen, 7803, N-5020, Bergen, Norway

    Helwig Hauser

  2. Fachbereich Informatik, Technische Universität Kaiserslautern, 3049, 67653, Kaiserslautern, Germany

    Hans Hagen

  3. Universität Bielefeld, Universität Bielefeld, 100131, 33501, Bielefeld, Germany

    Holger Theisel

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Laramee, R.S., Hauser, H., Zhao, L., Post, F.H. (2007). Topology-Based Flow Visualization, The State of the Art. In: Hauser, H., Hagen, H., Theisel, H. (eds) Topology-based Methods in Visualization. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70823-0_1

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