Image Annotation Refinement Using Web-Based Keyword Correlation

Authors:
Ainhoa Llorente;Enrico Motta;Stefan Rüger
Affiliations:
Knowledge Media Institute, The Open University, Milton Keynes, U.K. MK7 6AA;Knowledge Media Institute, The Open University, Milton Keynes, U.K. MK7 6AA;Knowledge Media Institute, The Open University, Milton Keynes, U.K. MK7 6AA
Venue:
SAMT '09 Proceedings of the 4th International Conference on Semantic and Digital Media Technologies: Semantic Multimedia
Year:
2009

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Abstract

This paper describes a novel approach that automatically refines the image annotations generated by a non-parametric density estimation model. We re-rank these initial annotations following a heuristic algorithm, which uses semantic relatedness measures based on keyword correlation on the Web. Existing approaches that rely on keyword co-occurrence can exhibit limitations, as their performance depend on the quality and coverage provided by the training data. Additionally, WordNet based correlation approaches are not able to cope with words that are not in the thesaurus. We illustrate the effectiveness of our Web-based approach by showing some promising results obtained on two datasets, Corel 5k, and ImageCLEF2009.