一种基于图的人脸特征提取方法

当前主流特征提取方法主要从全局特征或局部特征出发实现降维。为了能充分反映样本的全局特征和局部特征，提出基于图的人脸特征提取方法。该方法首先通过对训练样本进行学习得到最佳投影方向，该方向保证投影后的样本类内紧密而类间松散；然后将测试样本映射到最佳投影方向上并利用最近邻分类器进行样本类属判定。标准人脸库上的比较实验结果证明了所提方法的有效性。

Face feature extraction method based on graph

Current feature extraction methods are mainly based on global or local features. In order to fully utilize all the sample information, this paper presented Face Feature Extraction based on Graph (FFEG). At the training stage, the optimal projection was computed by learning the training samples, which guaranteed the samples within classes were close and between classes were far away. At the recognition stage, the test samples were successively mapped onto the optimal projection, and then the nearest neighbor classifier was used for classification and recognition. The experimental results on ORL dataset prove the effectiveness of the proposed method.