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A Linear-Algebraic Technique with an Application in Semantic Image Retrieval

Record type: Article

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.

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Citation

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, pp. 31-40. (doi:10.1007/11788034_4).

More information

Published date: 2006
Additional Information: Event Dates: 13th-15th July 2006
Venue - Dates: 5th International Conference on Image and Video Retrieval, 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
ORCID for Jonathon S. Hare: ORCID iD orcid.org/0000-0003-2921-4283

Catalogue record

Date deposited: 27 Jul 2006
Last modified: 18 Jul 2017 08:47

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Contributors

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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