Two- and three-dimensional patterns of the face
Two- and three-dimensional patterns of the face
Intelligent biometric techniques in fingerprint and face recognition
Intelligent biometric techniques in fingerprint and face recognition
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
3D Human Face Recognition Using Point Signature
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Cascade Architectures of Fuzzy Neural Networks
Fuzzy Optimization and Decision Making
Journal of Cognitive Neuroscience
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The depth information in the face represents personal features in detail. In particular, the surface curvatures extracted from the face contain the most important personal facial information. The principal component analysis using the surface curvature reduces the data dimensions with less degradation of original information, and the proposed 3D face recognition algorithm collaborated into them. The recognition for the eigenface referred from the maximum and minimum curvatures is performed. To classify the faces, the cascade architectures of fuzzy neural networks, which can guarantee a high recognition rate as well as parsimonious knowledge base, are considered. Experimental results on a 46 person data set of 3D images demonstrate the effectiveness of the proposed method.