郑州大学学报（工学版）2012，Vol.33Issue(3)：125-128,4.DOI:10.3969/j.issn.1671-6833.2012.03.032
基于类别多核局部判别嵌入的人脸识别
Face Recognition Based on Label Multiple Kernel Local Discriminant Embedding
王永茂 1徐正光 2吴金霞1
作者信息
- 1. 北京科技大学 自动化学院,北京100083
- 2. 河南理工大学 计算机科学与技术学院,河南焦作454003
- 折叠
摘要
Abstract
Based on local discriminant embedding, an efficient nonlinear subspace learning method, Label Multiple Kernel Local Discriminant Embedding (LMKLDE) , is developed. Firstly, according to the label information of given data set, local kernel function is defined and multiple kernel is gained. Then, different local kernel functions are merged by linear combination to form final kernel function. Finally, LMKLDE is developed by introducing label multiple kernel to LDE in order to deal with datasets of highly nonlinear structure. Experiments on ORL and Yale face database demonstrate the effectiveness of the proposed method.关键词
人脸识别/子空间学习/类别多核/降维Key words
face recognition/ subspace learning/ label multiple kernel/ dimensionality reduction分类
信息技术与安全科学引用本文复制引用
王永茂,徐正光,吴金霞..基于类别多核局部判别嵌入的人脸识别[J].郑州大学学报（工学版）,2012,33(3):125-128,4.
