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An ef?cient approach for face recognition based on common eigenvalues

机译：一种基于通用特征值的有效人脸识别方法

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摘要

In this paper, a simple technique is proposed for face recognition among many human faces. It is based on the polynomial coef?cients, covariance matrix and algorithm on common eigenvalues. The main advantage of the proposed approach is that the identi?cation of similarity between human faces is carried out without computing actual eigenvalues and eigenvectors. A symmetric matrix is calculated using the polynomial coef?cients-based companion matrices of two compared images. The nullity of a calculated symmetric matrix is used as similarity measure for face recognition. The value of nullity is very small for dissimilar images and distinctly large for similar face images. The feasibility of the propose approach is demonstrated on three face databases, i.e., the ORL database, the Yale database B and the FERET database. Experimental results have shown the effectiveness of the proposed approach for feature extraction and classi?cation of the face images having large variation in pose and illumination.
机译：在本文中，提出了一种用于在许多人脸之间进行人脸识别的简单技术。它基于多项式系数，协方差矩阵和常见特征值算法。该方法的主要优点是无需计算实际特征值和特征向量即可进行人脸之间相似度的识别。使用两个比较图像的基于多项式系数的伴随矩阵计算对称矩阵。计算出的对称矩阵的零值用作面部识别的相似性度量。对于不相似的图像，无效值非常小，而对于相似的面部图像，无效值非常大。在三个面部数据库即ORL数据库，Yale数据库B和FERET数据库上证明了该方法的可行性。实验结果表明，该方法对于姿态和光照变化较大的人脸图像的特征提取和分类是有效的。

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