计算机应用与软件Issue(10)：192-196,5.DOI:10.3969/j.issn.1000-386x.2014.10.046
融合约束采样和面部对齐的稀疏表示人脸识别
FACE RECOGNITION BASED ON SPARSE REPRESENTATION WITH FUSION OF CONSTRAINT SAMPLING AND FACE ALIGNMENT
刘晓飞1
作者信息
- 1. 山东外贸职业学院信息管理系 山东 青岛266071
- 折叠
摘要
Abstract
For the issue that face alignment is limited in traditional sparse representation classification method which will impact face rec-ognition rate,we propose a sparse representation classification method,it is based on constraint sampling and face alignment.First,we mark the training images in advance by using constraint sampling to get fixed face features.Then we do the face alignment and extract the features in combination with image texture information and shape features.Finally,we calculate the similarities between testing image and each train-ing image and use sparse representation classifier to complete the face recognition.The effectiveness and robustness of the proposed algorithm are verified by the experiments on face databases AR,CAS-PEAL and extended YaleB.Experimental results show that the combination of constraint sampling and face alignment greatly improves face recognition rate.This algorithm achieves better recognition effect than several other advanced robust face recognition algorithms.关键词
人脸识别/稀疏表示分类/约束采样/面部对齐/光照变化/面部伪装Key words
Face recognition/Sparse representation classification/Constraint sampling/Face alignment/Illustration variation/Facial masking分类
信息技术与安全科学引用本文复制引用
刘晓飞..融合约束采样和面部对齐的稀疏表示人脸识别[J].计算机应用与软件,2014,(10):192-196,5.
