View-dependent streamlines for 3D vector fields

Stéphane Marchesin, Cheng Kai Chen, Chris Ho, Kwan-Liu Ma

Research output: Contribution to journalArticlepeer-review

76 Scopus citations


This paper introduces a new streamline placement and selection algorithm for 3D vector fields. Instead of considering the problem as a simpl feature search in data space, we base our work on the observation that most streamline fields generate a lot of self-occlusion which prevents proper visualization. In order to avoid this issue, we approach the problem in a view-dependent fashion and dynamically determine a set of streamlines which contributes to data understanding without cluttering the view. Since our technique couples flow characteristic criteria and view-dependent streamline selection we are able achieve the best of both worlds: relevant flow description and intelligible, uncluttered pictures. We detail an efficient GPU implementation of our algorithm, show comprehensive visual results on multiple datasets and compare our method with existing flow depiction techniques. Our results show that our technique greatly improves the readability of streamline visualizations on different datasets without requiring user intervention.

Original languageEnglish (US)
Article number5613500
Pages (from-to)1578-1586
Number of pages9
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number6
StatePublished - Nov 12 2010


  • Streamlines
  • Vector fields
  • View-dependent

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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