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Iconizer: A framework to identify and create effective representations for visual information encoding

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The majority of visual communication today occurs by ways of spatial groupings, plots, graphs, data renderings, photographs and video frames. However, the degree of semantics encoded in these visual representations is still quite limited. The use of icons as a form of information encoding has been explored to a much lesser extent. In this paper we describe a framework that uses a dual domain approach involving natural language text processing and global image databases to help users identify icons suitable to visually encode abstract semantic concepts.

Original languageEnglish
Title of host publicationSmart Graphics - 11th International Symposium, SG 2011, Proceedings
Pages78-90
Number of pages13
DOIs
StatePublished - 2011
Event11th International Symposium on Smart Graphics, SG 2011 - Bremen, Germany
Duration: Jul 18 2011Jul 20 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6815 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Symposium on Smart Graphics, SG 2011
Country/TerritoryGermany
CityBremen
Period07/18/1107/20/11

Keywords

  • human-computer interaction
  • non-photorealistic rendering

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