Abstract
In this paper we propose an efficient method called the discriminative common vector method for face recognition. The discriminative common vectors representing each person in the training set of the face database are obtained by using the projection directions found in the null space of the within-class scatter matrix. Then, these vectors are used for classification of new faces. Also, an alternative algorithm based on the subspace methods is given to obtain the common vectors. Our test results show that the discriminative common vector method is superior to other methods in terms of recognition accuracy and efficiency.
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