| 基于Kernel PCA的人脸识别算法的探讨 |
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| 引用本文： | 张晓红,汤晓华,沈晓红.基于Kernel PCA的人脸识别算法的探讨[J].北京工商大学学报(自然科学版),2008,26(3):37-39. |
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| 作者姓名： | 张晓红 汤晓华 沈晓红 |
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| 作者单位： | 北京工商大学,机械自动化学院,北京,100037 |
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| 摘 要： | 扼要阐明抽取二维人脸图像特征方法并进行人脸识别,结合实验结果进行分析比较主元分析和核主元分析方法的优缺点,得出核主元分析方法在人脸识别算法中误识率低,解决了维数和小样本问题,能准确快速识别人脸的结论.
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| 关 键 词： | 人脸识别 主元分析法 核主元分析法 |
| 文章编号： | 1671-1513(2008)03-0037-03 |
| 修稿时间： | 2007年11月12 |
DISCUSSION ON FACE RECOGNITION ALGORITHM BASING ON KERNEL PCA |
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| ZHANG Xiao-hong,TANG Xiao-hua,SHEN Xiao-hong.DISCUSSION ON FACE RECOGNITION ALGORITHM BASING ON KERNEL PCA[J].Journal of Beijing Technology and Business University:Natural Science Edition,2008,26(3):37-39. |
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| Authors: | ZHANG Xiao-hong TANG Xiao-hua SHEN Xiao-hong |
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| Abstract: | Extracting and recognizing the 2-Dimension face feature are briefly expressed,combined with the investigation results on principle component analysis and kernel principle component analysis,which advantages and shortcomings are compared. The experiment finds that the KPCA algorithm on face recognition shows the good performance of lower error,resolves the problems of dimension and small sample system,and recognizes face accurately and quickly. |
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| Keywords: | face recognition principle component analysis kernel principle component analysis |
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