| 一种基于共同向量结合2DPCA的人脸识别方法 |
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| 引用本文： | 文颖,施鹏飞.一种基于共同向量结合2DPCA的人脸识别方法[J].自动化学报,2009,35(2):202-205. |
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| 作者姓名： | 文颖 施鹏飞 |
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| 作者单位： | 1.上海交通大学图像处理及模式识别研究所 上海 200030 |
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| 基金项目： | 国家高技术研究发展计划(863计划)，国家自然科学基金 |
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| 摘 要： | 提出了一种基于共同向量结合2维主成分分析(2-dimen-sional principal component analysis, 2DPCA)的人脸识别方法. 共同向量由图像通过Gram-Schmidt正交变换而求得, 具有该类图像共同不变的性质. 原始图像与该类共同向量之间的差分向量通过2DPCA处理, 依据最小距离测试得到识别结果. 实验在ORL和Yale人脸数据库进行测试, 结果表明本文提出的方法有较好的识别性能.
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| 关 键 词： | 人脸识别 共同向量 2维主成分分析 |
| 收稿时间： | 2007-7-2 |
| 修稿时间： | 2007-12-14 |
An Approach to Face Recognition Based on Common Vector and 2DPCA |
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| WEN Ying,SHI Peng-Fei.An Approach to Face Recognition Based on Common Vector and 2DPCA[J].Acta Automatica Sinica,2009,35(2):202-205. |
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| Authors: | WEN Ying SHI Peng-Fei |
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| Affiliation: | 1.Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200030 |
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| Abstract: | A novel approach to face recognition based on the common vector combined with 2-dimensional principal component analysis (2DPCA) is proposed in this paper. The common vector of one class is obtained by face images of the class processed by the Gram-Schmidt orthogonalization to represent the common invariant properties of the class. Recognition results are obtained by 2DPCA procedure and distance test of the difference vectors between the original image and the common vector of the class. Experiments are performed on ORL and Yale face databases and the results indicate that the proposed approach achieves good recognition results. |
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| Keywords: | Face recognition common vector 2-dimensional principal component analysis (2DPCA) |
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