关键词: 人脸识别, 特征提取, 奇异值分解, 小波分解, 特征融合矩阵

Abstract: In order to recognize face quickly and accurately，a weighted adaptive algorithm based on the conjunction of partial and entire features is proposed.Global features and local features of six key parts of face are extracted respectively by singular value to get the feature-matrix，dynamic method of how to choose the weights of local features and formula of how to obtain the feature-matrix is given and proved.Finally，the traditional Support Vector Machine（SVM） is improved to recognize the unknown faces.Experiments show that the proposed algorithm can not only calculate efficiently and work easily，but also deal with low recognition rate problems in SVD and small sample problems in LDA effectively，and the result indicates that it has a good performance and future.

Key words: face recognition, feature extraction, Singular Value Decomposition（SVD）, wavelet decomposition, feature-matrix