Task-based image annotation and retrieval

Dympna O'Sullivan, David Wilson, Michela Bertolotto, Eoin McLoughlin

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

Abstract

In order to address problems of information overload in digital imagery task domains we have developed an interactive approach to the capture and reuse of image context information. Our framework models different aspects of the relationship between images and domain tasks they support by monitoring the interactive manipulation and annotation of task-relevant imagery. The approach allows us to gauge a measure of a user's intentions as they complete goal-directed image tasks. As users analyze retrieved imagery their interactions are captured and an expert task context is dynamically constructed. This human expertise, proficiency, and knowledge can then be leveraged to support other users in carrying out similar domain tasks. We have applied our techniques to two multimedia retrieval applications for two different image domains, namely the geo-spatial and medical imagery domains.

Original languageEnglish
Title of host publicationRough Sets, Fuzzy Sets, Data Mining and Granular Computing - 11th International Conference, RSFDGrC 2007, Proceedings
PublisherSpringer Verlag
Pages451-458
Number of pages8
ISBN (Print)9783540725299
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computer, RSFDGrC 2007 - Toronto, Canada
Duration: 14 May 200717 May 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4482 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computer, RSFDGrC 2007
Country/TerritoryCanada
CityToronto
Period14/05/0717/05/07

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