| Laplace平滑变换及其在人脸识别中的应用 |
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| 引用本文： | 顾岁成,谭营,何新贵.Laplace平滑变换及其在人脸识别中的应用[J].中国科学：信息科学,2011(3). |
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| 作者姓名： | 顾岁成 谭营 何新贵 |
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| 作者单位： | 北京大学机器感知与智能教育部重点实验室;北京大学信息科学技术学院智能科学系; |
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| 基金项目： | 国家自然科学基金(批准号:60673020,60875080); 国家高技术研究发展计划(批准号:2007AA01Z453)资助项目 |
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| 摘 要： | 本文主要研究如何从最优化的角度出发,从图像中提取低频特征.首先,基于图像的局部梯度定义了一种图像频率,并基于这种定义,诱导出Laplace平滑变换(LST),将二维图像映射到一维的向量.然后,将LST与学习算法相结合,提出二步子空间学习算法.所提的基于LST的二步子空间方法,对于光照、表情、姿势具有鲁棒性.实验表明,在ORL,Yale和FERET人脸数据库上,基于LST的人脸识别算法,相对DCT,DWT和PCA等预处理算法,具有更小的识别误差.
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| 关 键 词： | Laplace平滑变换 人脸识别 主分量分析 余弦变换 小波变换 线性判别分析 |
Laplacian smoothing transform for face recognition |
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| Gu SuiCheng,Tan Ying, & He XinGui.Laplacian smoothing transform for face recognition[J].Scientia Sinica Informationis,2011(3). |
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| Authors: | Gu SuiCheng Tan Ying & He XinGui |
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| Affiliation: | Gu SuiCheng1,2,Tan Ying1,2 & He XinGui1,2 1 Department of Machine Intelligence,School of Electronics Engineering and Computer Science,Peking University,Beijing 100871,China,2 Key Laboratory of Machine Perception(MOE) |
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| Abstract: | In this paper,we investigate how to extract the lowest frequency features from an image.A novel laplacian smoothing transform(LST) is proposed to transform an image into a sequence,by which low frequency features of an image can be easily extracted for a discriminant learning method for face recognition.Generally,the LST is able to be a efficient dimensionality reduction method for face recognition problems.Extensive experimental results show that the LST method performs better than other pre-processing met... |
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| Keywords: | Laplacian smoothing transform(LST) face recognition principal component analysis(PCA) discrete cosine transform(DCT) discrete wavelet transform(DWT) linear discriminant analysis(LDA) |
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