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Image Auto-annotation using a Statistical Model with Salient Regions

Tang, Jiayu, Hare, Jonathon S. and Lewis, Paul H. (2006) Image Auto-annotation using a Statistical Model with Salient Regions At IEEE International Conference on Multimedia & Expo (ICME), Canada. 09 - 12 Jul 2006.

Record type: Conference or Workshop Item (Other)


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.

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Published date: 2006
Additional Information: Event Dates: 9-12 July
Venue - Dates: IEEE International Conference on Multimedia & Expo (ICME), Canada, 2006-07-09 - 2006-07-12
Organisations: Web & Internet Science


Local EPrints ID: 262826
ISBN: 1-4244-0367-7
PURE UUID: e6ee57d9-b800-4dd8-a045-db6883713860
ORCID for Jonathon S. Hare: ORCID iD

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Date deposited: 10 Jul 2006
Last modified: 18 Jul 2017 08:47

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Author: Jiayu Tang
Author: Paul H. Lewis

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