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Document Classification Using Multiple Views

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3 Author(s)
Albert Gordo ; Comput. Vision Center, Univ. Autonoma de Barcelona, Barcelona, Spain ; Florent Perronnin ; Ernest Valveny

The combination of multiple features or views when representing documents or other kinds of objects usually leads to improved results in classification (and retrieval) tasks. Most systems assume that those views will be available both at training and test time. However, some views may be too `expensive' to be available at test time. In this paper, we consider the use of Canonical Correlation Analysis to leverage `expensive' views that are available only at training time. Experimental results show that this information may significantly improve the results in a classification task.

Published in:

Document Analysis Systems (DAS), 2012 10th IAPR International Workshop on

Date of Conference:

27-29 March 2012