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Flow Visualization with Density Control

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Advances in Computer Graphics (CGI 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12221))

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Abstract

In flow visualization, it remains challenging to flexibly explore local regions in 3D fields and uniformly display the structures of flow fields while preserving key features. To this end, this paper presents a novel method for streamline generation and selection for 2D and 3D flow fields via density control. Several levels of streamlines are divided by flow density. The lowest level is produced using an entropy-based seeding strategy and a grid-based filling procedure. It can generate uniform streamlines without loss of important structural information. Other levels are then generated by a streamline selection algorithm based on the average distance among streamlines. It could help users understand flow fields in a more flexible manner. For 3D fields, we further provide local density control and density control along any axis for users, which are helpful to explore the fields both globally and locally. Various experimental results validate our method.

Supported by the Natural Science Foundation of China under grant nos. 61672375 and 61170118.

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Authors and Affiliations

  1. College of Intelligence and Computing, Tianjin University, Tianjin, 300350, People’s Republic of China

    Shiguang Liu & Hange Song

Authors
  1. Shiguang Liu
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  2. Hange Song
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Corresponding author

Correspondence to Shiguang Liu .

Editor information

Editors and Affiliations

  1. University of Geneva, Geneva, Switzerland

    Nadia Magnenat-Thalmann

  2. University of Crete, Heraklion, Greece

    Constantine Stephanidis

  3. University of Macau, Macau, China

    Enhua Wu

  4. Swiss Federal Institute of Technology, Lausanne, Switzerland

    Daniel Thalmann

  5. Shanghai Jiao Tong University, Shanghai, China

    Bin Sheng

  6. University of Sydney, Sydney, Australia

    Jinman Kim

  7. University of Crete, Heraklion, Greece

    George Papagiannakis

  8. University of Calgary, Calgary, AB, Canada

    Marina Gavrilova

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Liu, S., Song, H. (2020). Flow Visualization with Density Control. In: Magnenat-Thalmann, N., et al. Advances in Computer Graphics. CGI 2020. Lecture Notes in Computer Science(), vol 12221. Springer, Cham. https://doi.org/10.1007/978-3-030-61864-3_26

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  • DOI: https://doi.org/10.1007/978-3-030-61864-3_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61863-6

  • Online ISBN: 978-3-030-61864-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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