燕山大学学报2012，Vol.36Issue(6)：519-525,7.DOI:10.3969/j.issn.1007-791X.2012.06.009
基于特征联合和支持向量机的人脸识别
Face recognition based on features combination and SVM
摘要
Abstract
In order to further improve the face recognition rate in the case of taking into acount of the real-time, a novel face recognition method based on features combination and support vector machine is proposed. Firstly, the sample features of histograms of oriented gradients and local binary patterns are extracted and combined as the sample's combined features. Secondly, the principal component analysis method is adopted to reduce the dimension of the sample's combined features and the low dimensional combined features can be obtained. Finally, a support vector machine is trained by using the low dimensional combined features to form a face recognizer, and then the face recognizer is utilized to recognize the test samples. The experiments based on ORL face database show, compared with the existing methods, the proposed method can achieve better recognition rate and real-time.关键词
人脸识别/梯度方向直方图/局部二值模式/支持向量机/ORL人脸库Key words
face recognition/ histograms of oriented gradients/ local binary patterns/ support vector machine/ ORL face database分类
信息技术与安全科学引用本文复制引用
陈琦,郭顺超,张世辉..基于特征联合和支持向量机的人脸识别[J].燕山大学学报,2012,36(6):519-525,7.基金项目
河北省自然科学基金资助项目(F2010001276) （F2010001276）
