Canonical Correlation Analysis: An Overview with Application to Learning Methods

• DOI: 10.1162/0899766042321814
• Publication Date: 2004-10-26T22:27:03Z
• Authors: David R. Hardoon; Sandor Szedmak; John Shawe-Taylor
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; 004

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.