Tang, Jiayu and Lewis, Paul H.
Image Auto-annotation using 'Easy' and 'More Challenging' Training Sets.
At 7th International Workshop on Image Analysis for Multimedia Interactive Services, Hyatt Regency, Incheon International Airport, Korea,
19 - 21 Apr 2006.
Korea Information Science Society, .
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The Corel Image set is widely used for image annotation performance evaluation although it has been claimed that the set is easy to annotate. The aim of this paper is to demonstrate some of the disadvantages of sets like the Corel set for effective auto-annotation evaluation. We first compare the performanace of several annoatation algorithms using the Corel set and find that simple near neighbour propagation techniques perform almost as well as the best of the more sophisticated algorithms. We then build a new image collection using the Yahoo Image Search engine (http://images.yahoo.com) and uery-by-single-word searches to create a more challenging annotated set automatically. Then, using two very different image annotation methods, we demonstrate some of the problems of annotation using the Corel set compared with the Yahoo based training set. In both cases the training sets are used to create a set of annotations for the Corel test set. Finally we show how self-annotation can be used to improve the original annotations of our Yahoo set.
Available Versions of this Item
Image Auto-annotation using 'Easy' and 'More Challenging' Training Sets. (deposited 03 May 2006)
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