计算机应用与软件Issue(4)：175-177,3.DOI:10.3969/j.issn.1000-386x.2014.04.044
FLDA 在单样本人脸识别中的应用研究
ON APPLICATION OF FLDA IN SINGLE SAMPLE FACE RECOGNITION
马龙 1万康康 1韩小纯2
作者信息
- 1. 南京理工大学计算机科学与技术学院 江苏 南京 210094
- 2. 南京大学电子科学与工程学院 江苏 南京 210093
- 折叠
摘要
Abstract
With the constant development of face recognition technology,single sample face recognition has become today’s focus.In light of this issue,in the paper we present a face recognition method which is based on general frame learning.The method increases the total number of training samples of every class in the way of superimposing each single sample with a great deal of general samples in certain proportion,effectively utilises FLDA method to extract the features,and maps all the samples onto feature subspace,then makes use of the nearest neighbouring method to complete the face recognition,this mitigates the impacts of those factors including facial expression,attitude,illumination,etc.on recognition effect and raises recognition rate.The effectiveness of the proposed method has been verified on two major face libraries of ORL and Yale respectively.关键词
人脸识别/单训练样本/通用框架学习/Fisher线性判别分析Key words
Face recognition/Single training sample/General frame learning/Fisher linear discriminant analysis (FLDA)分类
信息技术与安全科学引用本文复制引用
马龙,万康康,韩小纯..FLDA 在单样本人脸识别中的应用研究[J].计算机应用与软件,2014,(4):175-177,3.
