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Single training sample face recognition(STSFR) is a tricky problem. It can cause a sharp decline in face recognition(FR) rate since each person only has one training sample. To solve this problem, a novel expanding sample method is proposed in this paper. Based on the fact that the intra-class facial variations can be shared across different persons, the intra-class facial variations are used to expand...
The sparse representation based classification (SRC) can effectively improve the face recognition rate. Smoothed l0 algorithm has much faster calculation speed and requires fewer measured values than the other sparse representation method. In this paper, the sparse representation and smoothed l0 algorithm for face recognition are presented to improve the face recognition under various conditions such...
In order to enhance the stability and security of biometric features recognition, the finger-knuckle-print (FKP) is used in this paper to study high performance recognition problem based on image set. After extracting the image feature by the method of local phase quantization, an image set can transform to a closely related set of points in the affine space. Then the models of the convex hulls are...
Fusion biometric recognition modal contributes in two aspects. It can not only improve the biometric recognition accuracy, but also gives a comparatively safe strategy, since it is difficult for intruders to achieve multi-biometric information simultaneously, especially the iris information. In this paper, a novel biometric fusion recognition modal with iris and facial images based on biomimetic pattern...
A novel partially occluded face recognition method based on biomimetic pattern recognition (BPR), proposed by academician Shoujue Wang, is proposed in this paper. A model for partially occluded face recognition based on BPR was introduced. An experiment based on biomimetic pattern recognition adopting a PCA and LDA feature extraction method is performed. Experimental results on Yale image database...
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