Mixture model for face-color modeling and segmentation

In this paper, we propose a general methodology for face-color modeling and segmentation. One of the major difficulties in face detection and retrieva l is partial face extraction due to highlights, shadows and lighting variat ions. We show that a mixture-of-Gaussians modeling of the color space, prov ides a robust representation that can accommodate large color variations, a s well as highlights and shadows. Our method enables to segment within-face regions, and associate semantic meaning to them, and provides statistical analysis and evaluation of the dominant variability within a given archive. (C) 2001 Elsevier Science B.V. All rights reserved.