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.
| Original language | English (US) |
|---|---|
| Article number | 6189339 |
| Pages (from-to) | 278-290 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Visualization and Computer Graphics |
| Volume | 19 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jan 1 2013 |
Fingerprint
Keywords
- focus+context
- nonlinear least squares optimization
- perception
- Resizing
- visualization framework
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Computer Graphics and Computer-Aided Design
Cite this
ViSizer : A visualization resizing framework. / Wu, Yingcai; Liu, Xiaotong; Liu, Shixia; Ma, Kwan-Liu.
In: IEEE Transactions on Visualization and Computer Graphics, Vol. 19, No. 2, 6189339, 01.01.2013, p. 278-290.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - ViSizer
T2 - A visualization resizing framework
AU - Wu, Yingcai
AU - Liu, Xiaotong
AU - Liu, Shixia
AU - Ma, Kwan-Liu
PY - 2013/1/1
Y1 - 2013/1/1
N2 - 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.
AB - 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.
KW - focus+context
KW - nonlinear least squares optimization
KW - perception
KW - Resizing
KW - visualization framework
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U2 - 10.1109/TVCG.2012.114
DO - 10.1109/TVCG.2012.114
M3 - Article
VL - 19
SP - 278
EP - 290
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
SN - 1077-2626
IS - 2
M1 - 6189339
ER -