Canonical Correlation Analysis: An Overview with Application to Learning Methods

Authors:
David R. Hardoon;Sandor R. Szedmak;John R. Shawe-taylor
Affiliations:
School of Electronics and Computer Science, Image, Speech and Intelligent Systems Research Group, University of Southampton, Southampton S017 1BJ, U.K.;School of Electronics and Computer Science, Image, Speech and Intelligent Systems Research Group, University of Southampton, Southampton S017 1BJ, U.K.;School of Electronics and Computer Science, Image, Speech and Intelligent Systems Research Group, University of Southampton, Southampton S017 1BJ, U.K.
Venue:
Neural Computation
Year:
2004

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Abstract

We present a general method using kernel canonical correlation analysis to learn a semantic representation to web images and their associated text. The semantic space provides a common representation and enables a comparison between the text and images. In the experiments, we look at two approaches of retrieving images based on only their content from a text query. We compare orthogonalization approaches against a standard cross-representation retrieval technique known as the generalized vector space model.