摘要
提出一种基于完全二维主元分析(2DPCA)的二次特征选择方法用于人脸识别。该方法针对PCA及其改进方法的不足,结合完全2DPCA方法,用免疫算法和基于最近邻分类器的5阶交叉验证方法完成对人脸特征二次选择。基于ORL人脸数据库和Yale人脸数据库的实验结果表明,该方法识别效果较好。
A second-order feature selection method based on complete 2DPCA is proposed for face recognition. The method based on complete 2DPCA uses immune algorithm and five-fold cross-validation method which is based on the nearest neighbor classifier to complete second-order selection of facial features in order to overcome the demerits of PCA and some improved PCA methods. Experiments based on ORL face library and Yale face library show that the method can achieve good recognition effect.
出处
《计算机工程》
CAS
CSCD
北大核心
2008年第3期223-224,227,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60475019)
关键词
人脸识别
完全二维主元分析
免疫算法
最近邻分类器
face recognition
complete Two-dimensional Principle Component Analysis（2DPCA）
immune algorithm
nearest neighbor classifier
