Mixture model for face-color modeling and segmentation

Hayit Greenspan*, Jacob Goldberger, Itay Eshet

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

96 Scopus citations


In this paper, we propose a general methodology for face-color modeling and segmentation. One of the major difficulties in face detection and retrieval is partial face extraction due to highlights, shadows and lighting variations. We show that a mixture-of-Gaussians modeling of the color space, provides a robust representation that can accommodate large color variations, as 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.

Original languageEnglish
Pages (from-to)1525-1536
Number of pages12
JournalPattern Recognition Letters
Issue number14
StatePublished - Dec 2001


  • Face segmentation
  • Face-color modeling
  • Gaussian mixture
  • Skin color modeling


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