Face Recognition Based on Locally Linear Embedding and Least Squares Support Vector Machines

TAN Shu-cai; HUANG Jing-tao

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Face Recognition Based on Locally Linear Embedding and Least Squares Support Vector Machines

更新时间：2026-09-04

- Face Recognition Based on Locally Linear Embedding and Least Squares Support Vector Machines
- Vol. 27, Issue 7, Pages: 110-113(2010)
- 作者机构：
  
  河南科技大学机构电子信息工程学院,河南,洛阳,471003
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2010
- 稿件说明：
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谈书才, 黄景涛. 基于LLE和LS-SVM的人脸识别方法[J]. 微电子学与计算机, 2010, 27(7): 110-113.

TAN Shu-cai, HUANG Jing-tao. Face Recognition Based on Locally Linear Embedding and Least Squares Support Vector Machines[J]. 2010, 27(7): 110-113.
谈书才, 黄景涛. 基于LLE和LS-SVM的人脸识别方法[J]. 微电子学与计算机, 2010, 27(7): 110-113. DOI：

TAN Shu-cai, HUANG Jing-tao. Face Recognition Based on Locally Linear Embedding and Least Squares Support Vector Machines[J]. 2010, 27(7): 110-113. DOI：

摘要

为了提高人脸识别的速度

提出了一种基于局部线性嵌套(LLE)和最小二乘支持向量机(LS-SVM)的人脸识别方法.该方法采用主成分分析(PCA)和LLE相结合的算法

对归一化处理过的人脸图像进行特征提取

利用LS-SVM对人脸图像样本集进行训练和识别

以提高识别的速度.最后将本文方法在ORL人脸数据库上进行试验

结果表明

人脸识别的速度有了一定的提高

识别率达到了90%以上.

Abstract

In order to improve the speed of face recognition

a face recognition method based on locally linear embedding (LLE) and least squares support vector machines (LS-SVM) was proposed. After extracting the features of the pre-processing face images using principal component analysis (PCA) and locally linear embedding

LS-SVM was used to train the feature sets and recognize the faces. And

the speed of face recognition was improved. Finally

the method was tested on the ORL (Olivetti Research Laboratory) face database

the results show that the proposed method can improve the speed of face recognition

and the rate of face recognition exceeds 90%.

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Related Author

YANG Ying-xian

Related Institution

Department of Information Management, Guangdong Justice Police Vocational College

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