关键词: 人脸识别, 有监督近邻保持嵌入（SNPE）, 支持向量机（SVM）

Abstract: For face recognition，most of traditional methods which reduce the high dimensional data are linear.Support Vector Machine can enhance the generation ability of study，and can overcome the disadvantage of overfitting.The paper proposes a method for face recognition based Supervised Neighborhood Preserving（SNPE） and Support Vector Machine（SVM）.The K of NPE is confirmed with supervised mode.SNPE aims at preserving the local manifold structure.Also，comparing to the recently proposed manifold learning algorithms such as Locally Linear Embedding，SNPE is defined everywhere，rather than only on the training data points，and it’s more applied.With SVM framework for multiple sequences，experiment results on ORL database demonstrate the algorithm is fast，steady and effective.

Key words: face recognition, Supervised Neighborhood Preserving Embedding（SNPE）, Support Vector Machine（SVM）