Presents a robust and precise scheme for face detection and precise facial feature location. Multiscale filters are used to obtain the pre-attentive features of objects, based on which different models are investigated to locate the face and facial features such as eyes, nose and mouth. The structural model is used to characterize the geometric pattern of facial components. The texture and feature models are used to verify the face candidates detected before. Since the eyeballs are the only features that are salient and have strong invariant property, the distance between them is used to normalize faces for recognition. Motivated from this, with the face detected and the structural information extracted, a precise eyes location algorithm is applied using contour and region information. It detects, with a subpixellic precision, the center and the radius of the eyeballs of a person. The detected result can be used as an accurate normalization of images, which reduces greatly the number of possible scales used during the face recognition process.
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