An orthogonal subspace projection approach for face recognition

Face recognition has been widely used to automatically identify and verify a person. In this paper, we proposed a new approach based on orthogonal subspace projection (OSP) to identification of human faces. In linear mixture model of the face images, the OSP faces of the training images are calculated by using orthogonal subspace projection approach and the signal-to noise ratio maximization. And the weight parameter of the input image is obtained to do face recognition.

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