引用本文: | 文益民,范志刚.判决特征选择的快速人脸识别算法[J].国防科技大学学报,2009,31(3):87-91.[点击复制] |
WEN Yimin,FAN Zhigang.Discriminative Feature Selection for Fast Face Recognition[J].Journal of National University of Defense Technology,2009,31(3):87-91[点击复制] |
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判决特征选择的快速人脸识别算法 |
文益民1,2, 范志刚3 |
(1.湖南大学 电气与信息工程学院,湖南 长沙 410082;2.湖南工业职业技术学院 信息工程系,湖南 长沙 410208;3.上海交通大学 计算机系,上海 200240)
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摘要: |
为了在确保识别精度的条件下提高人脸识别的速度,提出了判决特征选择算法(SVM-DFS)。针对多类分类问题,判决特征选择算法根据统计学习理论使用支持向量机来实现特征选择,根据全概率定理把特征选择和多类分类集成到一个统一框架。在UMIST和FERET人脸数据库上的实验表明:SVM-DFS算法可以用来挑选对分类最有用的特征,这些挑选出来的特征具有明显的物理意义。使用判决特征选择方法不但可以加快分类器的响应速度,而且不降低分类器的泛化能力。 |
关键词: 判决特征 学习系统 支持向量机 人脸识别 |
DOI: |
投稿日期:2009-04-14 |
基金项目:国家863计划资助项目(2007AA04Z244);国家自然科学基金重点资助项目(60835004);湖南省博士后科研资助专项计划资助项目(2008RS4005) |
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Discriminative Feature Selection for Fast Face Recognition |
WEN Yimin1,2, FAN Zhigang3 |
(1.College of Electrical and Information Engineering, Hunan Univ., Changsha 410082, China;2.2.Department of Information Engineering, Hunan Industry Polytechnic, Changsha 410208, China;3.Department of Computer, Shanghai Jiao Tong Univ., Shanghai 200240, China)
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Abstract: |
In order to speed up the face recognition algorithm under the condition of keeping high accuracy, a discriminative feature selection algorithm is proposed to handle multi-class face recognition problems. It is supported by vector machine to select features and employ total probability rule to integrate feature selection and multi-class classification into an integral frame. The experiment on the face databases of UMIST and FERET displays that the proposed algorithm can effectively select the features which have obvious physical meanings, thus speeding up the response of classifier without degrading the generalization performance. |
Keywords: discriminative feature learning systems support vector machines face recognition |
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