Context-Preserving Visual Links

Abstract

Evaluating, comparing, and interpreting related pieces of information are tasks that are commonly performed during visual data analysis and in many kinds of information-intensive work. Synchronized visual highlighting of related elements is a well-known technique used to assist this task. An alternative approach, which is more invasive but also more expressive is visual linking in which line connections are rendered between related elements. In this work, we present context-preserving visual links as a new method for generating visual links. The method specifically aims to fulfill the following two goals: first, visual links should minimize the occlusion of important information; second, links should visually stand out from surrounding information by minimizing visual interference. We employ an image-based analysis of visual saliency to determine the important regions in the original representation. A consequence of the image-based approach is that our technique is application-independent and can be employed in a large number of visual data analysis scenarios in which the underlying content cannot or should not be altered. We conducted a controlled experiment that indicates that users can find linked elements in complex visualizations more quickly and with greater subjective satisfaction than in complex visualizations in which plain highlighting is used. Context-preserving visual links were perceived as visually more attractive than traditional visual links that do not account for the context information.

Citation

Markus Steinberger, Manuela Waldner, Marc Streit, Alexander Lex, Dieter Schmalstieg
Context-Preserving Visual Links
IEEE Transactions on Visualization and Computer Graphics (InfoVis'11), 17(12): 2249--2258, doi:10.1109/TVCG.2011.183, 2011.
 IEEE InfoVis 2011 Best Paper Award

BibTeX

@article{2011_infovis_context-preserving-links,
  title = {Context-Preserving Visual Links},
  author = {Markus Steinberger and Manuela Waldner and Marc Streit and Alexander Lex and Dieter Schmalstieg},
  journal = {IEEE Transactions on Visualization and Computer Graphics (InfoVis'11)},
  doi = {10.1109/TVCG.2011.183},
  volume = {17},
  number = {12},
  pages = {2249--2258},
  year = {2011}
}
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