Coherent time-varying graph drawing with multifocus+context interaction

Kun Chuan Feng, Chaoli Wang, Han Wei Shen, Tong Yee Lee

Research output: Contribution to journalArticle

27 Citations (Scopus)

Abstract

We present a new approach for time-varying graph drawing that achieves both spatiotemporal coherence and multifocus+context visualization in a single framework. Our approach utilizes existing graph layout algorithms to produce the initial graph layout, and formulates the problem of generating coherent time-varying graph visualization with the focus+context capability as a specially tailored deformation optimization problem. We adopt the concept of the super graph to maintain spatiotemporal coherence and further balance the needs for aesthetic quality and dynamic stability when interacting with time-varying graphs through focus+context visualization. Our method is particularly useful for multifocus+context visualization of time-varying graphs where we can preserve the mental map by preventing nodes in the focus from undergoing abrupt changes in size and location in the time sequence. Experiments demonstrate that our method strikes a good balance between maintaining spatiotemporal coherence and accentuating visual foci, thus providing a more engaging viewing experience for the users.

Original languageEnglish
Article number5963661
Pages (from-to)1330-1342
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
Volume18
Issue number8
DOIs
Publication statusPublished - 2012 Apr 24

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Drawing (graphics)
Visualization
Experiments

All Science Journal Classification (ASJC) codes

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

Cite this

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Coherent time-varying graph drawing with multifocus+context interaction. / Feng, Kun Chuan; Wang, Chaoli; Shen, Han Wei; Lee, Tong Yee.

In: IEEE Transactions on Visualization and Computer Graphics, Vol. 18, No. 8, 5963661, 24.04.2012, p. 1330-1342.

Research output: Contribution to journalArticle

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