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.

Publication Date



Journal Webpage: http://www.elsevier.com/wps/find/journaldescription.cws_home/505619/description#descriptionNote: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type


Department, Program, or Center

Microelectronic Engineering (KGCOE)


RIT – Main Campus