[1]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(03):125-128.[doi:10.3969/j.issn.1671-6833.2012.03.032]
 WANG Yongmao,XU Zhengguang,WU Jinxia.Face Recognition Based on Label Multiple Kernel Locat Discriminant Embedding[J].Journal of Zhengzhou University (Engineering Science),2012,33(03):125-128.[doi:10.3969/j.issn.1671-6833.2012.03.032]
点击复制

基于类别多核局部判别嵌入的人脸识别()
分享到:

《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
33
期数:
2012年03期
页码:
125-128
栏目:
出版日期:
2012-05-10

文章信息/Info

Title:
Face Recognition Based on Label Multiple Kernel Locat Discriminant Embedding
作者:
王永茂徐正光吴金霞.
北京科技大学 自动化学院,北京100083;河南理工大学 计算机科学与技术学院,河南焦作454003, 北京科技大学 自动化学院,北京,100083
Author(s):
WANG YongmaoXU ZhengguangWU Jinxia
1.School of Automation, University of Seience and Technology af Beijing, Beijing 100083, Chinn;2. Sehool of Computer Sei.ence and Technology, Henan Polytechnie University, Jiaozuo 454003, China
关键词:
人脸识别 子空间学习 类别多核 降维
Keywords:
face recognition subspace leaming label multiple kemel dimensionality reduction
分类号:
TP391.4
DOI:
10.3969/j.issn.1671-6833.2012.03.032
摘要:
在局部判别嵌入的基础上提出了一种有效的非线性子空间学习方法:类别多核局部判别嵌入.首先针对给定数据的类别信息,定义基于每一个类别的局部核函数,形成多核,接着将不同的局部核函数进行线性组合作为最终的核函数引入到局部判别嵌入算法中,得到类别多核局部判别嵌入算法,在核空间内提取图像高阶非线性信息.在ORL和Yale库上的人脸识别表明该方法是有效的.
Abstract:
Based on loeal discriminant embedding, an efficient nonlinear subspace leaming method, LabelMuliple Kemel local Discriminant Embedding ( LMKLDE ) , is developed, Firstly, according to the label in-formation of given data set, local kerel function is defined and multiple kernel is gained, Then, different lo-eal kerel funetions are merged by linear combination to form final kernel funetion. Finally, LMKiDE is de-veloped by introducing label multiple kernel to LDE in order to deal with datasets of highly nonlinear struc.ture. Experiments on ORL, and Yale face database demonstrate the effectiveness of the proposed method.

相似文献/References:

[1]张勇党兰学.线性判别分析特征提取稀疏表示人面识别方法[J].郑州大学学报(工学版),2015,36(02):94.[doi:10.3969/ j.issn.1671 -6833.2015.02.021]
 ZHANG Yong,DANG Lan-xue.Sparse Representation-based Face RecognitionMethod by LDA Feature Extraction[J].Journal of Zhengzhou University (Engineering Science),2015,36(03):94.[doi:10.3969/ j.issn.1671 -6833.2015.02.021]
[2]蔡金收,陈铁军,郭丽.基于投票极限学习机的人脸识别混合算法研究[J].郑州大学学报(工学版),2016,37(02):37.[doi:10.3969/j.issn.1671-6833.201505016]
 Chen Tiejun,Cai Jinshou,Guo Li.Research on Hybrid Face Recognition Algorithm Based on Voting Extreme Learning Machine[J].Journal of Zhengzhou University (Engineering Science),2016,37(03):37.[doi:10.3969/j.issn.1671-6833.201505016]
[3]苏士美,王燕,王明霞.基于加权小波分解的人脸识别算法研究[J].郑州大学学报(工学版),2014,35(01):5.[doi:10.3969/j.issn.1671-6833.2014.01.002]
 SU Shimei,WANG Yan,WANG Mingxia.Face Recognition Research Based on Weighted Wavelet Decomposition[J].Journal of Zhengzhou University (Engineering Science),2014,35(03):5.[doi:10.3969/j.issn.1671-6833.2014.01.002]
[4]段向军,王敏..基于改进的奇异值和遗传算法的人脸识别研究[J].郑州大学学报(工学版),2010,31(04):69.[doi:10.3969/j.issn.1671-6833.2010.04.017]

更新日期/Last Update: 1900-01-01