Retrieving Keyword's to an Image Query using Kernel CCA
David R. Hardoon, Sandor Szedmak and John Shawe-Taylor
University of Southampton, Southampton, UK.
In this paper we propose an approach to automatically annotate queryimages with keywords. We use kernel Canonical Correlation Analysis to learn a semantic representation between images and their associateddocuments. The semantic space provides a common representation and enables a comparison between the documents and images. This represen-tation is then used in the creation of new document, comprised from the keywords that best fit the image query. We compare our method againsta standard cross-representation retrieval technique known as Generalised Vector Space Model.