We present an inherently discriminative approach to face recognition. This is achieved by automatically selecting key points from lines that sketch the face and extracting textural information at these locations. As the distribution of the lines depend on each individual face, the selected points will be person-dependent, achieving discrimination in an early stage of the recognition process. A robust shape matching algorithm has been used for the correspondence problem, and Gabor responses have been extracted at final points so that both shape and textural information are combined to measure similarities between faces. Face verification results are reported over the well known XM2VTS database.
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