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Showing papers on "Eigenface published in 1993"


Journal ArticleDOI
TL;DR: Various low-dimensional representations of the faces in the higher dimensions of the face space (i.e., the eigenvectors with smaller eigenvalues) provide better information for face recognition.
Abstract: Faces can be represented efficiently as a weighted linear combination of the eigenvectors of a covariance matrix of face images. It has also been shown [ J. Opt. Soc. Am.4, 519– 524 ( 1987)] that identifiable faces can be made by using only a subset of the eigenvectors, i.e., those with the largest eigenvalues. This low-dimensional representation is optimal in that it minimizes the squared error between the representation of the face image and the original face image. The present study demonstrates that, whereas this low-dimensional representation is optimal for identifying the physical categories of face, like sex, it is not optimal for recognizing the faces (i.e., discriminating known from unknown faces). Various low-dimensional representations of the faces in the higher dimensions of the face space (i.e., the eigenvectors with smaller eigenvalues) provide better information for face recognition.

221 citations


Journal ArticleDOI
TL;DR: An X Windows software tool for the construction of faces with a weighted combination of eigenvectors is described in this paper, where the weights were extracted from an auto-associative matrix that comprised 100 face images.
Abstract: An X Windows software tool for the construction of faces with a weighted combination of eigenvectors is described The eigenvectors were extracted from an autoassociative matrix that comprised 100 face images The program input consists of eigenvectors and sets of weights that describe individual faces and combines these to create face images The tool creates a panel of buttons that permits the display of individual eigenvectors and the display of an average face as well Facilities for on-line changes to the intensity of individual eigenvectors can be used to change the appearance of a face Previously, O’Toole, Abdi, Deffenbacher, and Bartlett (1991) have shown that the intensity of certain individual eigenvectors contains reliable information for determining the sex and race of the face

6 citations