Task-based image annotation and retrieval

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

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

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
Subtitle of host publication11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007. Proceedings
EditorsAijun An, Jerzy Stefanowski, Sheela Ramanna, Cory J. Butz, Witold Pedrycz, Guoyin Wang
Place of PublicationBerlin (DE)
PublisherSpringer
Pages451-458
Number of pages8
ISBN (Electronic)978-3-540-72530-5
ISBN (Print)978-3-540-72529-9
DOIs
Publication statusPublished - 2007
Event11th International Conference, RSFDGrC 2007 - Toronto, Canada
Duration: 14 May 200716 May 2007

Publication series

NameLecture notes in computer science
PublisherSpringer
Volume4482
ISSN (Print)0302-9743

Conference

Conference11th International Conference, RSFDGrC 2007
CountryCanada
CityToronto
Period14/05/0716/05/07

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Gages
Monitoring

Cite this

O'Sullivan, D., Wilson, D., Bertolotto, M., & McLoughlin, E. (2007). Task-based image annotation and retrieval. In A. An, J. Stefanowski, S. Ramanna, C. J. Butz, W. Pedrycz, & G. Wang (Eds.), Rough sets, fuzzy sets, data mining and granular computing: 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007. Proceedings (pp. 451-458). (Lecture notes in computer science ; Vol. 4482). Berlin (DE): Springer. https://doi.org/10.1007/978-3-540-72530-5_54
O'Sullivan, Dympna ; Wilson, David ; Bertolotto, Michela ; McLoughlin, Eoin. / Task-based image annotation and retrieval. Rough sets, fuzzy sets, data mining and granular computing: 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007. Proceedings. editor / Aijun An ; Jerzy Stefanowski ; Sheela Ramanna ; Cory J. Butz ; Witold Pedrycz ; Guoyin Wang. Berlin (DE) : Springer, 2007. pp. 451-458 (Lecture notes in computer science ).
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O'Sullivan, D, Wilson, D, Bertolotto, M & McLoughlin, E 2007, Task-based image annotation and retrieval. in A An, J Stefanowski, S Ramanna, CJ Butz, W Pedrycz & G Wang (eds), Rough sets, fuzzy sets, data mining and granular computing: 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007. Proceedings. Lecture notes in computer science , vol. 4482, Springer, Berlin (DE), pp. 451-458, 11th International Conference, RSFDGrC 2007, Toronto, Canada, 14/05/07. https://doi.org/10.1007/978-3-540-72530-5_54

Task-based image annotation and retrieval. / O'Sullivan, Dympna; Wilson, David ; Bertolotto, Michela; McLoughlin, Eoin.

Rough sets, fuzzy sets, data mining and granular computing: 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007. Proceedings. ed. / Aijun An; Jerzy Stefanowski; Sheela Ramanna; Cory J. Butz; Witold Pedrycz; Guoyin Wang. Berlin (DE) : Springer, 2007. p. 451-458 (Lecture notes in computer science ; Vol. 4482).

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

TY - GEN

T1 - Task-based image annotation and retrieval

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AU - Wilson, David

AU - Bertolotto, Michela

AU - McLoughlin, Eoin

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N2 - 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.

AB - 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.

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O'Sullivan D, Wilson D, Bertolotto M, McLoughlin E. Task-based image annotation and retrieval. In An A, Stefanowski J, Ramanna S, Butz CJ, Pedrycz W, Wang G, editors, Rough sets, fuzzy sets, data mining and granular computing: 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007. Proceedings. Berlin (DE): Springer. 2007. p. 451-458. (Lecture notes in computer science ). https://doi.org/10.1007/978-3-540-72530-5_54