Item

Abstract

Several models for parameterized face representations have been
proposed in the last years. A simple coding scheme treats the image of
a face as a long vector with each entry coding for the intensity of
one single pixel in the image (e.g. Sirovich Kirby 1987). Although
simple and straightforward, such pixel-based representations have
several disadvantages. We propose a representation for images of
faces that separates texture and 2D shape by exploiting pixel-by-pixel
correspondence between the images. The advantages of this
representation compared to pixel-based representations are
demonstrated by means of the quality of low-dimensional
reconstructions derived from principal component analysis and by means
of the performance that a simple linear classifier can achieve for sex
classification.