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中文摘要：
PCA（Principal Component Analysis）,主成分分析方法,是一种得到广泛应用的人脸识别方法。PCA算法提供了一个高维和低维空间的线性变换矩阵,就是利用低维特征向量来表示原始样本信息,利用变换矩阵可以得到一个特征子空间,即特征脸。进行识别时,把待识别的人脸向其投影,采用最近邻法得到最近的点,最终识别该人的身份。
英文摘要：
PCA（Principal Component Analysis） is the most used method in human face recognition.PCA algorithm can get the linear transformation matrix which transform a high-dimensional to low-dimensional space,can approximate the original data with lower dimension feature vector.This transformation matrix can be used to obtain a subspace（eigenfaces）.When identifying,the face is projected to the subspace,using nearest neighbor method has been a recent point in order to identify the identity of the person.
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