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Facing the reality of semantic image retrieval

Facing the reality of semantic image retrieval
Facing the reality of semantic image retrieval
Purpose – To provide a better-informed view of the extent of the semantic gap in image retrieval, and the limited potential for bridging it offered by current semantic image retrieval techniques. Design/methodology/approach – Within an ongoing project, a broad spectrum of operational image retrieval activity has been surveyed, and, from a number of collaborating institutions, a test collection assembled which comprises user requests, the images selected in response to those requests, and their associated metadata. This has provided the evidence base upon which to make informed observations on the efficacy of cutting-edge automatic annotation techniques which seek to integrate the text-based and content-based image retrieval paradigms. Findings – Evidence from the real-world practice of image retrieval highlights the existence of a generic-specific continuum of object identification, and the incidence of temporal, spatial, significance and abstract concept facets, manifest in textual indexing and real-query scenarios but often having no directly visible presence in an image. These factors combine to limit the functionality of current semantic image retrieval techniques, which interpret only visible features at the generic extremity of the generic-specific continuum. Research limitations/implications – The project is concerned with the traditional image retrieval environment in which retrieval transactions are conducted on still images which form part of managed collections. The possibilities offered by ontological support for adding functionality to automatic annotation techniques are considered. Originality/value – The paper offers fresh insights into the challenge of migrating content-based image retrieval from the laboratory to the operational environment, informed by newly-assembled, comprehensive, live data.
Information retrieval, Resource description languages, Semantics, Visual databases
465-481
Enser, Peter G. B.
3d0430bb-861f-4d99-a2d7-be7935d5a6c5
Sandom, Christine J.
6637df2a-0204-4e48-951c-6a95e661627d
Hare, Jonathon S.
65ba2cda-eaaf-4767-a325-cd845504e5a9
Lewis, Paul H.
7aa6c6d9-bc69-4e19-b2ac-a6e20558c020
Enser, Peter G. B.
3d0430bb-861f-4d99-a2d7-be7935d5a6c5
Sandom, Christine J.
6637df2a-0204-4e48-951c-6a95e661627d
Hare, Jonathon S.
65ba2cda-eaaf-4767-a325-cd845504e5a9
Lewis, Paul H.
7aa6c6d9-bc69-4e19-b2ac-a6e20558c020

Enser, Peter G. B., Sandom, Christine J., Hare, Jonathon S. and Lewis, Paul H. (2007) Facing the reality of semantic image retrieval Journal of Documentation, 63, (4), pp. 465-481.

Record type: Article

Abstract

Purpose – To provide a better-informed view of the extent of the semantic gap in image retrieval, and the limited potential for bridging it offered by current semantic image retrieval techniques. Design/methodology/approach – Within an ongoing project, a broad spectrum of operational image retrieval activity has been surveyed, and, from a number of collaborating institutions, a test collection assembled which comprises user requests, the images selected in response to those requests, and their associated metadata. This has provided the evidence base upon which to make informed observations on the efficacy of cutting-edge automatic annotation techniques which seek to integrate the text-based and content-based image retrieval paradigms. Findings – Evidence from the real-world practice of image retrieval highlights the existence of a generic-specific continuum of object identification, and the incidence of temporal, spatial, significance and abstract concept facets, manifest in textual indexing and real-query scenarios but often having no directly visible presence in an image. These factors combine to limit the functionality of current semantic image retrieval techniques, which interpret only visible features at the generic extremity of the generic-specific continuum. Research limitations/implications – The project is concerned with the traditional image retrieval environment in which retrieval transactions are conducted on still images which form part of managed collections. The possibilities offered by ontological support for adding functionality to automatic annotation techniques are considered. Originality/value – The paper offers fresh insights into the challenge of migrating content-based image retrieval from the laboratory to the operational environment, informed by newly-assembled, comprehensive, live data.

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More information

Published date: August 2007
Keywords: Information retrieval, Resource description languages, Semantics, Visual databases
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 264377
URI: http://eprints.soton.ac.uk/id/eprint/264377
PURE UUID: fe4ebe3b-8623-46e6-83f9-93c82e360454
ORCID for Jonathon S. Hare: ORCID iD orcid.org/0000-0003-2921-4283

Catalogue record

Date deposited: 03 Aug 2007
Last modified: 18 Jul 2017 07:36

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Contributors

Author: Peter G. B. Enser
Author: Christine J. Sandom
Author: Paul H. Lewis

University divisions

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