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
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;
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
DOI :
10.1109/TVCG.2012.114