Abstract
Recognition of human faces out of still images or image sequences is a research field of fast increasing interest. At first, facial regions and facial features like eyes and mouth have to be extracted. In the present paper we propose an approach that copes with problems of these first two steps. We perform face localization based on the observation that human faces are characterized by their oval shape and skin-color, also in the case of varying light conditions. For that we segment faces by evaluating shape and color (HSV) information. Then face hypotheses are verified by searching for facial features inside of the face-like regions. This is done by applying morphological operations and minima localization to intensity images.
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