Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-27T16:17:30.187Z Has data issue: false hasContentIssue false
  • English
  • Français

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 [email protected] www.utdallas.edu/~herve Université de Bourgogne, 21004 Dijon Cedex, [email protected] www.u-bourgogne.fr/abdi
Dominique Valentin
Affiliation:
The University of Texas at Dallas, School of Human Development, Richardson, TX 75083-0688 [email protected] www.utdallas.edu/~herve Université de Bourgogne, 21004 Dijon Cedex, [email protected] www.u-bourgogne.fr/abdi
Betty G. Edelman
Affiliation:
Université de Bourgogne, 21004 Dijon Cedex, [email protected] www.u-bourgogne.fr/abdi
Get access Rights & Permissions [Opens in a new window]

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)