A Linear-Algebraic Technique with an Application in Semantic Image Retrieval
A Linear-Algebraic Technique with an Application in Semantic Image Retrieval
This paper presents a novel technique for learning the underlying structure that links visual observations with semantics. The technique, inspired by a text-retrieval technique known as cross-language latent semantic indexing uses linear algebra to learn the semantic structure linking image features and keywords from a training set of annotated images. This structure can then be applied to unannotated images, thus providing the ability to search the unannotated images based on keyword. This factorisation approach is shown to perform well, even when using only simple global image features.
Image Annotation, Semantic Image Retrieval, SVD, Semantic Space
3-540-36018-2
31-40
Hare, Jonathon S.
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Lewis, Paul H.
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Enser, Peter G. B.
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Sandom, Christine J.
6637df2a-0204-4e48-951c-6a95e661627d
Sundaram, Hari
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Naphade, Milind
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Smith, John R.
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Rui, Yong
5c6b5a8c-44d7-452e-b3eb-48f7c28d93aa
2006
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
Sundaram, Hari
abd00f33-4f11-41e2-b211-350f2a7c02e6
Naphade, Milind
ea7ca447-b738-4920-ba23-61b59698c1bd
Smith, John R.
d8deba04-0754-45ef-9ee6-aa19a711a744
Rui, Yong
5c6b5a8c-44d7-452e-b3eb-48f7c28d93aa
Hare, Jonathon S., Lewis, Paul H., Enser, Peter G. B. and Sandom, Christine J.
,
Sundaram, Hari, Naphade, Milind, Smith, John R. and Rui, Yong
(eds.)
(2006)
A Linear-Algebraic Technique with an Application in Semantic Image Retrieval.
Lecture Notes in Computer Science, LNCS 4, .
(doi:10.1007/11788034_4).
Abstract
This paper presents a novel technique for learning the underlying structure that links visual observations with semantics. The technique, inspired by a text-retrieval technique known as cross-language latent semantic indexing uses linear algebra to learn the semantic structure linking image features and keywords from a training set of annotated images. This structure can then be applied to unannotated images, thus providing the ability to search the unannotated images based on keyword. This factorisation approach is shown to perform well, even when using only simple global image features.
Text
JH_CIVR2006_Factorisation_Springer.pdf
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More information
Published date: 2006
Additional Information:
Event Dates: 13th-15th July 2006
Venue - Dates:
5th International Conference on Image and Video Retrieval, Tempe, Arizona, United States, 2006-07-13 - 2006-07-15
Keywords:
Image Annotation, Semantic Image Retrieval, SVD, Semantic Space
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 262870
URI: http://eprints.soton.ac.uk/id/eprint/262870
ISBN: 3-540-36018-2
ISSN: 0302-9743
PURE UUID: cf6003e3-058f-4558-b4cf-7ca3c75be5ae
Catalogue record
Date deposited: 27 Jul 2006
Last modified: 15 Mar 2024 03:25
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Contributors
Author:
Jonathon S. Hare
Author:
Paul H. Lewis
Author:
Peter G. B. Enser
Author:
Christine J. Sandom
Editor:
Hari Sundaram
Editor:
Milind Naphade
Editor:
John R. Smith
Editor:
Yong Rui
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