| 基于偏最小二乘分析的人脸表示与识别 |
| |
| 引用本文： | 孙权森,陈强,夏德深.基于偏最小二乘分析的人脸表示与识别[J].江南大学学报(自然科学版),2008,7(1):1-5. |
| |
| 作者姓名： | 孙权森 陈强 夏德深 |
| |
| 作者单位： | 南京理工大学,计算机科学与技术学院,江苏,南京,210094 |
| |
| 基金项目： | 国家自然科学基金项目(60773172)，江苏省“青蓝工程”资助项目 |
| |
| 摘 要： | 基于偏最小二乘回归分析,提出了一种新的人脸表示与重构方法.与主成分分析相比,通过偏最小二乘所抽取的低维人脸表示特征具有更好的分类性能.在ORL人脸数据库上的实验结果表明,基于偏最小二乘方法对于测试图像进行重构优于主成分分析方法,并且分类结果也好于后者.
|
| 关 键 词： | 偏最小二乘 主成分分析 人脸表示 人脸识别 |
| 文章编号： | 1671-7147(2008)01-0001-05 |
| 修稿时间： | 2007年10月8日 |
Face Representation and Recognition Using Partial Least Squares Regression |
| |
| SUN Quan-sen,CHEN Qiang,XIA De-shen.Face Representation and Recognition Using Partial Least Squares Regression[J].Journal of Southern Yangtze University:Natural Science Edition,2008,7(1):1-5. |
| |
| Authors: | SUN Quan-sen CHEN Qiang XIA De-shen |
| |
| Abstract: | The partial least squares(PLS) regression is a new multivariate data analysis method developed from practical applications in real word.In this paper,a new face representation and the recognition method based on PLS model is presented.In contrast to principal component analysis(PCA),the process of extracting lower-dimensional face representation features by PLS contains the class information of samples and has better classification performance.The experimental results on ORL face image database have shown that when the testing images are reconstructed,PLS-based methods are superior to PCA-based ones,and the former classification results is better than the latter. |
| |
| Keywords: | partial least squares principal component analysis face representation face recognition |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
