• DocumentCode
    9772
  • Title

    ViSizer: A Visualization Resizing Framework

  • Author

    Wu, Yingcai ; Liu, Xiaotong ; Liu, Shixia ; Ma, Kwan-Liu

  • Author_Institution
    Dept. of Comput. Sci., Univ. of California, Davis, Davis, CA, USA
  • Volume
    19
  • Issue
    2
  • fYear
    2013
  • fDate
    Feb. 2013
  • Firstpage
    278
  • Lastpage
    290
  • Abstract
    Visualization resizing is useful for many applications where users may use different display devices. General resizing techniques (e.g., uniform scaling) and image-resizing techniques suffer from several drawbacks, as they do not consider the content of the visualizations. This work introduces ViSizer, a perception-based framework for automatically resizing a visualization to fit any display. We formulate an energy function based on a perception model (feature congestion), which aims to determine the optimal deformation for every local region. We subsequently transform the problem into an optimization problem by the energy function. An efficient algorithm is introduced to iteratively solve the problem, allowing for automatic visualization resizing.
  • Keywords
    data visualisation; display devices; image processing; least squares approximations; optimisation; ViSizer; display device; energy function; feature congestion; general resizing technique; image-resizing technique; nonlinear least squares optimization; optimal deformation; optimization problem; perception model; perception-based framework; uniform scaling; visualization resizing framework; Clutter; Context; Data visualization; Ellipsoids; Layout; Optimization; Visualization; Resizing; focus+context; nonlinear least squares optimization; perception; visualization framework;
  • fLanguage
    English
  • Journal_Title
    Visualization and Computer Graphics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1077-2626
  • Type

    jour

  • DOI
    10.1109/TVCG.2012.114
  • Filename
    6189339