Canonical correlation analysis: an overview with application to learning methods

  • Hardoon D
  • Szedmak S
  • Shawe-Taylor J
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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.

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  • D R Hardoon

  • S Szedmak

  • J Shawe-Taylor

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