| 基于人脸重要特征和SVM的人脸识别方法 |
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| 引用本文： | 董李艳,胡海平,赵丛. 基于人脸重要特征和SVM的人脸识别方法[J]. 应用数学与计算数学学报, 2008, 22(1) |
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| 作者姓名： | 董李艳 胡海平 赵丛 |
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| 作者单位： | 1. 上海大学理学院数学系,上海,200444
2. 西北工业大学应用数学系,西安,710072 |
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| 摘 要： | 提出了一种基于人脸重要特征的人脸识别方法,首先选取人脸的重要特征并将其具体化,对得到的重要特征进行主成分分析,然后用支持向量机(Support Vector Machine,SVM)设计重要特征分类器来确定测试人脸图像中重要特征,同时设计支持向量机(SVM)人脸分类器,确定人脸图像的所属类别.对ORL人脸图像数据库进行仿真实验,结果表明,该方法要优于一般的基于整体特征的人脸识别方法并有较强的鲁棒性.
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| 关 键 词： | 人脸识别 支持向量机 主成分分析 人脸图像 整体特征 识别方法 Support Vector Machine Features Face Based Method 鲁棒性 结果 仿真实验 图像数据库 类别 同时设计 确定测试 分类器 支持向量机 主成分分析 选取 |
A Face Recognition Method Based on Face Important Features and Support Vector Machine |
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| Dong Liyan,Hu Haiping,Zhao Cong. A Face Recognition Method Based on Face Important Features and Support Vector Machine[J]. Communication on Applied Mathematics and Computation, 2008, 22(1) |
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| Authors: | Dong Liyan Hu Haiping Zhao Cong |
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| Affiliation: | Dong Liyan~1 Hu Haiping~1 Zhao Cong~2 Department of Mathematics,Shanghai University,Shanghai 200444,China Department of Applied Mathematics,Northwest Polytechnical University,Xi'an 710072,China. |
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| Abstract: | A method for face recognition based on face important features proposed in this paper.At first selecting face important feature of regional and then the principle component analysis (PCA) coefficients are extracted as feature vectors from the face component image,then support vector machine (SVM) is used to train features and face recognition machine.Features classification machine distinguishes the component regions in the face image,and face classification machine determines which person the image should ... |
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| Keywords: | face recognition support vector machine principle component analysis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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