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Conference Proceeding

Publication Date



Image annotation research has demonstrated success on test data for focused domains. Unfortunately, extending these techniques to the broader topics found in real world data often results in poor performance. This paper proposes a novel approach that leverages WordNet and ImageNet capabilities to annotate images based on local text and image features. Signatures generated from ImageNet images based on WordNet synonymous sets are compared using Earth Mover's Distance against the query image and used to rank order surrounding words by relevancy. The results demonstrate effective image annotation, producing higher accuracy and improved specificity over the ALIPR image annotation system. Abstract © AAAI.


Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved.

AFIT Scholar furnishes a draft of this conference paper.

Source Publication

26th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2013