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Eigenfeatures as intermediate-level representations: The case for PCA models

Published online by Cambridge University Press:  01 February 1998

Hervé Abdi ,
Dominique Valentin  and
Betty G. Edelman
Hervé Abdi
Affiliation:
The University of Texas at Dallas, School of Human Development, Richardson, TX 75083-0688 herve@utdallas.edu www.utdallas.edu/~herve Université de Bourgogne, 21004 Dijon Cedex, Franceherve.abdi@u-bourgogne.fr www.u-bourgogne.fr/abdi
Dominique Valentin
Affiliation:
The University of Texas at Dallas, School of Human Development, Richardson, TX 75083-0688 herve@utdallas.edu www.utdallas.edu/~herve Université de Bourgogne, 21004 Dijon Cedex, Franceherve.abdi@u-bourgogne.fr www.u-bourgogne.fr/abdi
Betty G. Edelman
Affiliation:
Université de Bourgogne, 21004 Dijon Cedex, Franceherve.abdi@u-bourgogne.fr www.u-bourgogne.fr/abdi
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Abstract

Eigenfeatures are created by the principal component approach (PCA) used on objects described by a low-level code (i.e., pixels, Gabor jets). We suggest that eigenfeatures act like the flexible features described by Schyns et al. They are particularly suited for face processing and give rise to class-specific effects such as the other-race effect. The PCA approach can be modified to accommodate top-down constraints.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 21 , Issue 1 , February 1998 , pp. 17 - 18
Copyright
© 1998 Cambridge University Press

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