基于降维的人脸识别方法研究与应用

Face recognition method based on dimensionality reduction and its application

人脸识别是计算机视觉识别研究热点问题之一。研究了基于降维的人脸识别方法,利用主成分分析和核主成分分析对人脸图像降维,通过实验分析降维对人脸识别准确率的影响。在两个人脸图像数据集上的实验表明,降维可以提高人脸识别准确率,核主成分分析在人脸识别研究中更有优势。

Face recognition is one of the hot topics in computer vision recognition.In this paper,a face recognition method based on dimensionality reduction is proposed.Principal component analysis and kernel principal component analysis are used to reduce the dimensionality of face images,and the influence of dimensionality reduction on face recognition accuracy is analyzed by experiment.The experiments on two face image data sets show that dimensionality reduction can improve the accuracy of face recognition,and kernel principal component analysis is more advantageous in face recognition research.