Scalable visualization resizing framework

Yingcai Wu, Kwan-Liu Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish (US)
Title of host publicationScalable Integration of Analytics and Visualization - Papers from the 2011 AAAI Workshop, Technical Report
Pages51-53
Number of pages3
VolumeWS-11-17
StatePublished - Nov 2 2011
Event2011 AAAI Workshop - San Francisco, CA, United States
Duration: Aug 7 2011Aug 7 2011

Other

Other2011 AAAI Workshop
CountryUnited States
CitySan Francisco, CA
Period8/7/118/7/11

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'Scalable visualization resizing framework'. Together they form a unique fingerprint.

  • Cite this

    Wu, Y., & Ma, K-L. (2011). Scalable visualization resizing framework. In Scalable Integration of Analytics and Visualization - Papers from the 2011 AAAI Workshop, Technical Report (Vol. WS-11-17, pp. 51-53)