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Saliency-based Models of Image Content and their Application to Auto-Annotation by Semantic Propagation

Record type: Conference or Workshop Item (Other)

In this paper, we propose a model of automatic image annotation based on propagation of keywords. The model works on the premise that visually similar image content is likely to have similar semantic content. Image content is extracted using local descriptors at salient points within the image and quantising the feature-vectors into visual terms. The visual terms for each image are modelled using techniques taken from the information retrieval community. The modelled information from an unlabelled query image is compared to the models of a corpus of labelled images and labels are propagated from the most similar labelled images to the query image.

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Citation

Hare, Jonathon S. and Lewis, Paul H. (2005) Saliency-based Models of Image Content and their Application to Auto-Annotation by Semantic Propagation At Multimedia and the Semantic Web / European Semantic Web Conference 2005.

More information

Published date: 2005
Additional Information: Event Dates: 29/5/2005
Venue - Dates: Multimedia and the Semantic Web / European Semantic Web Conference 2005, 2005-05-29
Keywords: Saliency, auto-annotation, vector-space, latent semantic indexing
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 260954
URI: http://eprints.soton.ac.uk/id/eprint/260954
PURE UUID: 92ed07e7-5d40-46dd-a3a1-3af106e377da
ORCID for Jonathon S. Hare: ORCID iD orcid.org/0000-0003-2921-4283

Catalogue record

Date deposited: 24 Jun 2005
Last modified: 18 Jul 2017 09:06

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Contributors

Author: Paul H. Lewis

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