| 保持拓扑性非负矩阵分解法在人脸识别的应用 |
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| 引用本文： | 何光辉,张太平.保持拓扑性非负矩阵分解法在人脸识别的应用[J].计算机工程与应用,2010,46(14):202-204. |
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| 作者姓名： | 何光辉 张太平 |
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| 作者单位： | 1. 重庆大学,数理学院,重庆,400030
2. 重庆大学,计算机学院,重庆,400030 |
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| 摘 要： | 提出了一种用于人脸识别新的保持拓扑性非负矩阵分解方法。该方法通过将梯度距离最小化来发现人脸模式内在的流型结构。与PCA、LDA和最初的NMF方法相比较，保持拓扑性非负矩阵分解法发现一种嵌入来保留局部拓扑信息，比如边缘和质地。该文提出的保持拓扑性非负矩阵分解法对在有光照下的面部表情的变化有效。实验结果表明该方法提供了一种更好的脸部表示模式，同时也提高了人脸识别正确率。
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| 关 键 词： | 人脸识别 非负矩阵分解 保持拓扑性 |
| 收稿时间： | 2008-11-11 |
| 修稿时间： | 2009-3-13
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Face recognition based on topology preserving nonnegative matrix factorization |
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| HE Guang-hui,ZHANG Tai-ping.Face recognition based on topology preserving nonnegative matrix factorization[J].Computer Engineering and Applications,2010,46(14):202-204. |
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| Authors: | HE Guang-hui ZHANG Tai-ping |
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| Affiliation: | 1.College of Mathematics and Physics,Chongqing University,Chongqing 400030,China 2.College of Computer Science,Chongqing University,Chongqing 400030,China |
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| Abstract: | A novel Topology Preserving Nonnegative Matrix Factorization(TPNMF) method is proposed for face recognition.The TPNMF is based on minimizing the constraint gradient distance,compared with L2 distance,the gradient distance is able to reveal latent manifold structure of face patterns.Compared with PCA,LDA and original NMF which search only the Euclidean structure of face space,TPNMF finds an embedding that preserves local topology information,such as edges and texture.In the way,the proposed TPNMF method is r... |
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| Keywords: | face recognition Nonnegative Matrix Factorization(NMF) topology preserving |
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