Dynamic label sampling on fisheye maps for information exploration

ABSTRACT

For data with large dimensionality, placing labels is critical for users' comprehension of a scatterplot or a map of items. We propose a dynamic label sampling technique that, combined with graphical fisheye views, selects appropriate labels out of a large set of items on a map. Labels are sampled to give focus and contextual information according to users' panning/zooming and filtering operation. The paper also demonstrates an example of visual exploration with the image browser based on our technique.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS

Additional Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)
          Subjects: Interaction styles (e.g., commands, menus, forms, direct manipulation)

  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.6 Methodology and Techniques
          Subjects: Interaction techniques

General Terms:
Design, Human Factors, Management, Performance, Theory

Keywords:
browsing, fisheye view, information exploration, information visualization, label sampling, map labeling