Automated image annotation using global features and robust nonparametric density estimation

Authors:
Alexei Yavlinsky;Edward Schofield;Stefan Rüger
Affiliations:
Department of Computing, Imperial College London, London, UK;Department of Computing, Imperial College London, London, UK;Department of Computing, Imperial College London, London, UK
Venue:
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Year:
2005

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Abstract

This paper describes a simple framework for automatically annotating images using non-parametric models of distributions of image features. We show that under this framework quite simple image properties such as global colour and texture distributions provide a strong basis for reliably annotating images. We report results on subsets of two photographic libraries, the Corel Photo Archive and the Getty Image Archive. We also show how the popular Earth Mover’s Distance measure can be effectively incorporated within this framework.