| 基于鲁棒稀疏表示的人脸识别算法 |
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| 引用本文： | 曹振亮.基于鲁棒稀疏表示的人脸识别算法[J].电子技术,2014(6):1-3. |
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| 作者姓名： | 曹振亮 |
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| 作者单位： | 曲阜师范大学信息技术与传播学院 |
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| 摘 要： | 提出了一种基于LBP算子和鲁棒稀疏表示的人脸识别方法。首先,提取训练样本和测试样本的LBP特征。其次,在原有稀疏表示分类器(SRC)的基础上添加一个权值矩阵W来解决l1正则化最小二乘问题。最后,利用鲁棒稀疏表示分类器(RSRC)分类测试人脸图像所属类别。在ATT人脸库上进行实验的结果表明,此方法是优于其他经典算法的。
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| 关 键 词： | 人脸识别 LBP算子 稀疏表示 RSRC |
Face Recognition Based on Robust Sparse Representation |
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| Cao Zhenliang.Face Recognition Based on Robust Sparse Representation[J].Electronic Technology,2014(6):1-3. |
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| Authors: | Cao Zhenliang |
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| Institution: | Cao Zhenliang (Information Technology and Communication College, Qufu Normal University) |
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| Abstract: | This paper proposes a new face recognition method based on LBP operator and RSR （Robust Sparse Representation）. Firstly, the LBP features of the training data and testing data are extracted. Secondly, on the basis of SRC, a weighted matrix W is added to solve a ll-regularized least square problem. Finally, RSRC is used to judge which class the face images belong to. Experimental results on AT＆T database demonstrate the new method has very good performance and superior over other classical methods. |
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| Keywords: | face recognition LBP operator sparse representation RSRC |
| 本文献已被 CNKI 维普 等数据库收录！ |
