Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of Methods for Ridge and Valley Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ridges, Valleys and Hausdorff Based Similarity Measures for Face Description and Matching
PRIS '01 Proceedings of the 1st International Workshop on Pattern Recognition in Information Systems: In conjunction with ICEIS 2001
Distinctiveness of faces: A computational approach
ACM Transactions on Applied Perception (TAP)
Recognition of human faces: from biological to artificial vision
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
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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.