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.
Department, Program, or Center
Microelectronic Engineering (KGCOE)
Saber, E. & Tekalp, A., "Facial pattern detection and eye localization using color, shape and symmetry-based cost functions," Pattern Recognition Letters, vol. 19, pp. 669-680. (1998)
RIT – Main Campus