Automatic annotation of images from the practitioner perspective

Authors:
Peter G. B. Enser;Christine J. Sandom;Paul H. Lewis
Affiliations:
School of Computing, Mathematical and Information Sciences, University of Brighton;School of Computing, Mathematical and Information Sciences, University of Brighton;Department of Electronics and Computer Science, University of Southampton
Venue:
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Year:
2005

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Abstract

This paper describes an ongoing project which seeks to contribute to a wider understanding of the realities of bridging the semantic gap in visual image retrieval. A comprehensive survey of the means by which real image retrieval transactions are realised is being undertaken. An image taxonomy has been developed, in order to provide a framework within which account may be taken of the plurality of image types, user needs and forms of textual metadata. Significant limitations exhibited by current automatic annotation techniques are discussed, and a possible way forward using ontologically supported automatic content annotation is briefly considered as a potential means of mitigating these limitations.