SineStream: Improving the Readability of Streamgraphs by Minimizing Sine Illusion Effects

  • Chuan Bu
  • , Quanjie Zhang
  • , Qianwen Wang
  • , Jian Zhang
  • , Michael Sedlmair
  • , Oliver Deussen
  • , Yunhai Wang

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

In this paper, we propose SineStream, a new variant of streamgraphs that improves their readability by minimizing sine illusion effects. Such effects reflect the tendency of humans to take the orthogonal rather than the vertical distance between two curves as their distance. In SineStream, we connect the readability of streamgraphs with minimizing sine illusions and by doing so provide a perceptual foundation for their design. As the geometry of a streamgraph is controlled by its baseline (the bottom-most curve) and the ordering of the layers, we re-interpret baseline computation and layer ordering algorithms in terms of reducing sine illusion effects. For baseline computation, we improve previous methods by introducing a Gaussian weight to penalize layers with large thickness changes. For layer ordering, three design requirements are proposed and implemented through a hierarchical clustering algorithm. Quantitative experiments and user studies demonstrate that SineStream improves the readability and aesthetics of streamgraphs compared to state-of-the-art methods.

Original languageEnglish (US)
Article number9222035
Pages (from-to)1634-1643
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Volume27
Issue number2
DOIs
StatePublished - Feb 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Readability
  • Sine Illusion
  • Streamgraphs

Fingerprint

Dive into the research topics of 'SineStream: Improving the Readability of Streamgraphs by Minimizing Sine Illusion Effects'. Together they form a unique fingerprint.

Cite this