Frontal-view face detection and facial feature extraction using color, shape and symmetry based cost functions

  • Authors:
  • Eli Saber;A. Murat Tekalp

  • Affiliations:
  • Department of Electrical Engineering and Center for Electronic Imaging Systems, University of Rochester, Rochester, NY 14627-0126, USA and Xerox Corporation, 800 Phillips Road, Building 200-01A, W ...;Department of Electrical Engineering and Center for Electronic Imaging Systems, University of Rochester, Rochester, NY 14627-0126, USA

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 1998

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Abstract

We describe an algorithm for detecting human faces and facial features, such as the location of the eyes, nose and mouth. First, a supervised pixel-based color classifier is employed to mark all pixels that are within a prespecified distance of ''skin color'', which is computed from a training set of skin patches. This color-classification map is then smoothed by Gibbs random field model-based filters to define skin regions. An ellipse model is fit to each disjoint skin region. Finally, we introduce symmetry-based cost functions to search the center of the eyes, tip of nose, and center of mouth within ellipses whose aspect ratio is similar to that of a face.