Taking image as matrix, an eigenface algorithm uses eigenvalues and corresponding eigenvectors in recognition. The algorithm has advantage of no need of extracting geometric features of eyes, noses and mouths, but doesn't reach high recognition rate when single sample image per person is used for training. Another problem is that the larger the number of face modes is, the more complex the computation becomes. In this paper, an algorithm is proposed taking multi samples as sub modes and grouped face modes...
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