Image Auto-annotation using a Statistical Model with Salient Regions
Image Auto-annotation using a Statistical Model with Salient Regions
Traditionally, statistical models for image auto-annotation have been coupled with image segmentation. Considering the performance of the current segmentation algorithms, it can be meaningful to avoid a segmentation stage. In this paper, we propose a new approach to image auto-annotation using statistical models. In this approach, segmentation is avoided through the use of salient regions. The use of the statistical model results in an annotation performance which improves upon our previously proposed saliency-based word propagation technique. We also show that the use of salient regions achieves better results than the use of general image regions or segments.
1-4244-0367-7
Tang, Jiayu
4f9409ac-830d-4937-867d-e06c76b8a4e1
Hare, Jonathon S.
65ba2cda-eaaf-4767-a325-cd845504e5a9
Lewis, Paul H.
7aa6c6d9-bc69-4e19-b2ac-a6e20558c020
2006
Tang, Jiayu
4f9409ac-830d-4937-867d-e06c76b8a4e1
Hare, Jonathon S.
65ba2cda-eaaf-4767-a325-cd845504e5a9
Lewis, Paul H.
7aa6c6d9-bc69-4e19-b2ac-a6e20558c020
Tang, Jiayu, Hare, Jonathon S. and Lewis, Paul H.
(2006)
Image Auto-annotation using a Statistical Model with Salient Regions.
IEEE International Conference on Multimedia & Expo (ICME), Hilton Toronto, Toronto, Ontario, Canada.
09 - 12 Jul 2006.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Traditionally, statistical models for image auto-annotation have been coupled with image segmentation. Considering the performance of the current segmentation algorithms, it can be meaningful to avoid a segmentation stage. In this paper, we propose a new approach to image auto-annotation using statistical models. In this approach, segmentation is avoided through the use of salient regions. The use of the statistical model results in an annotation performance which improves upon our previously proposed saliency-based word propagation technique. We also show that the use of salient regions achieves better results than the use of general image regions or segments.
More information
Published date: 2006
Additional Information:
Event Dates: 9-12 July
Venue - Dates:
IEEE International Conference on Multimedia & Expo (ICME), Hilton Toronto, Toronto, Ontario, Canada, 2006-07-09 - 2006-07-12
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 262826
URI: http://eprints.soton.ac.uk/id/eprint/262826
ISBN: 1-4244-0367-7
PURE UUID: e6ee57d9-b800-4dd8-a045-db6883713860
Catalogue record
Date deposited: 10 Jul 2006
Last modified: 15 Mar 2024 03:25
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Contributors
Author:
Jiayu Tang
Author:
Jonathon S. Hare
Author:
Paul H. Lewis
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