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Communication Dans Un Congrès Année : 2010

A union of incoherent spaces model for classification

Karin Schnass
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  • PersonId : 884521
Pierre Vandergheynst
  • Fonction : Auteur
  • PersonId : 839985

Résumé

We present a new and computationally efficient scheme for classifying signals into a fixed number of known classes. We model classes as subspaces in which the corresponding data is well represented by a dictionary of features. In order to ensure low misclassification, the subspaces should be incoherent so that features of a given class cannot represent efficiently signals from another. We propose a simple iterative strategy to learn dictionaries which are are the same time good for approximating within a class and also discriminant. Preliminary tests on a standard face images database show competitive results.

Dates et versions

inria-00568895 , version 1 (23-02-2011)

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Citer

Karin Schnass, Pierre Vandergheynst. A union of incoherent spaces model for classification. Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on, Mar 2010, Dallas, United States. pp.5490 -5493, ⟨10.1109/ICASSP.2010.5495208⟩. ⟨inria-00568895⟩
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