Abstract
Effective visualization resizing is important for many visualization tasks, where users may have display devices with different sizes and aspect ratios. Our recently designed framework can adapt a visualization to different displays by transforming the resizing problem into a non-linear optimization problem. However, it is not scalable to a large amount of dense information. Undesired cluttered results would be produced if dense information is presented in the target display. We present an extension to our resizing framework with a seamless integration of a sampling-based data abstraction mechanism, such that it is scalable with not only different display sizes, but also different amounts of information.
| Original language | English (US) |
|---|---|
| Title of host publication | Scalable Integration of Analytics and Visualization - Papers from the 2011 AAAI Workshop, Technical Report |
| Pages | 51-53 |
| Number of pages | 3 |
| Volume | WS-11-17 |
| State | Published - Nov 2 2011 |
| Event | 2011 AAAI Workshop - San Francisco, CA, United States Duration: Aug 7 2011 → Aug 7 2011 |
Other
| Other | 2011 AAAI Workshop |
|---|---|
| Country | United States |
| City | San Francisco, CA |
| Period | 8/7/11 → 8/7/11 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Scalable visualization resizing framework. / Wu, Yingcai; Ma, Kwan-Liu.
Scalable Integration of Analytics and Visualization - Papers from the 2011 AAAI Workshop, Technical Report. Vol. WS-11-17 2011. p. 51-53.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Scalable visualization resizing framework
AU - Wu, Yingcai
AU - Ma, Kwan-Liu
PY - 2011/11/2
Y1 - 2011/11/2
N2 - Effective visualization resizing is important for many visualization tasks, where users may have display devices with different sizes and aspect ratios. Our recently designed framework can adapt a visualization to different displays by transforming the resizing problem into a non-linear optimization problem. However, it is not scalable to a large amount of dense information. Undesired cluttered results would be produced if dense information is presented in the target display. We present an extension to our resizing framework with a seamless integration of a sampling-based data abstraction mechanism, such that it is scalable with not only different display sizes, but also different amounts of information.
AB - Effective visualization resizing is important for many visualization tasks, where users may have display devices with different sizes and aspect ratios. Our recently designed framework can adapt a visualization to different displays by transforming the resizing problem into a non-linear optimization problem. However, it is not scalable to a large amount of dense information. Undesired cluttered results would be produced if dense information is presented in the target display. We present an extension to our resizing framework with a seamless integration of a sampling-based data abstraction mechanism, such that it is scalable with not only different display sizes, but also different amounts of information.
UR - http://www.scopus.com/inward/record.url?scp=80055033757&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80055033757&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:80055033757
SN - 9781577355335
VL - WS-11-17
SP - 51
EP - 53
BT - Scalable Integration of Analytics and Visualization - Papers from the 2011 AAAI Workshop, Technical Report
ER -