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Previous works have demonstrated that manifold-based learning discriminant approaches can improve the face recognition accuracy. However, they ignore the variation among nearby face images from the same class, which is important to further improve the recognition accuracy and avoid the over-fitting problem in discriminant approaches. To avoid this problem, we propose a novel approach for face recognition...
This paper presents a two-dimensional Neighborhood Preserving Projection (2DNPP) for appearance-based face representation and recognition. 2DNPP enables us to directly use a feature input of 2D image matrices rather than 1D vectors. We use the same neighborhood weighting procedure that is involved in NPP to form the nearest neighbor affinity graph. Theoretical analysis of the connection between 2DNPP...
Unimodal biometric systems contend with a variety of problems such as noisy data, restricted degrees of freedom, non-universality and spoof attacks. Some of these limitations can be overcome by employing multi-modal biometric identification technologies. The paper discusses a new multi-modal biometrics based on face and ear. The research significance of multi-modal biometrics based on face and ear...
Ear recognition is a new research area in the computer vision and pattern recognition field. This paper proposes a new ear biometrics system-compound structure classifier system for ear recognition (CSCSER), based on the research of ear recognition with algebraic feature. The system first makes rough classification to the human ears according to their geometric features. Then the algebra features...
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