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2003-2021 全部
为您找到包含“二维主成分分析”的内容共7

Wang Haixian

Principal component analysis (PCA), as one of the most popular unsupervised dimensionality reduction methods, is of importance in multivariate data analysis. It seeks a set of orthogonal bases such that the variance of the input data points is maximized. The conventional PCA, however, is sensitive to outliers due to the utilization of L2-norm. As a robust alternative to PCA, PCA-L1 is proposed in literature. In image domain, two-dimensional PCA (2DPCA) is directly based on image matrices, obviating the image-to-vector transformation as in PCA. Likewise, 2DPCA uses L2-norm, and 2DPCA-L1, proposed in literature, is the robust version of 2DPCA. PCA-L1 and 2DPCA-L1 are two important subspace learning approaches developed recently. In this paper, we show that 2DPCA-L1 is in fact a special case of PCA-L1 applying to row vectors of image matrices. Thus, the relationship between these two methods is made clear.

2011-01-12

This work was supported by Specialized Research Fund for the Doctoral Program of Higher Education of China under grant(20070286030

Research Center for Learning Science, Southeast University

#Computer Science and Technology#

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刘丽倩,刘岚,刘玲

2010-11-15

)及其改进算法二维成分分析(2DPCA)方法进行了理论研究,并通过MATLAB仿真进行了性能比较,实验表明2DPCA识别率更高,识别时间更短。

武汉理工大学信息学院,武汉理工大学信息学院,武汉理工大学信息学院

#电子、通信与自动控制技术#

0评论(0 分享(0)

李晨昊,蒋砚军

2014-12-19

集中的图片较多导致矩阵计算量大,因此基于PCA算法的人脸识别耗时较长,不适合单机串行运行。本文针对PCA算法的这一缺点,综合了基于二维矩阵处理的二维成分分析(2DPCA)算法,提出了一种单机基于GPU

北京邮电大学计算机学院,北京 100037,北京邮电大学计算机学院,北京 100037

#计算机科学技术#

0评论(0 分享(0)

林森,王鑫磊

2020-06-29

自适应多重均匀局部二值模式(WA-MULBP)与二维成分分析(two dimensional principal component analysis, 2DPCA)相结合的掌纹识别方法?首先采用直方图

辽宁省教育厅科学研究项目(LJ2019JL022

辽宁省自然科学基金面上项目(L2014132

辽宁省自然科学基金指导计划项目(2015020100

Automation and Electrical Engineering school, Shenyang Ligong University, Shenyang 110159,Electronic and Information Engineering School, Liaoning Technical University, Huludao 125105

#电子、通信与自动控制技术#

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程永强,杨冰

2011-03-08

本文提出一种基于二维Gabor小波特征矩阵的增强2DPCA人脸识别算法。该算法利用了Gabor小波变换对位置和光线的不敏感性及良好的纹理提取特性,以二维Gabor小波矩阵描述人脸特征。使用增强2DPCA方法进行特征降维,先对二维Gabor小波矩阵做行方向的2DPCA变换,再对生成的特征矩阵进行列方向的2DPCA变换。分别在ORL人脸库和Yale人脸库采用最近邻分类器进行试验,结果表明该方法性能优良,具有较高的识别率。

太原理工大学信息学院,太原理工大学信息学院

#计算机科学技术#

2评论(0 分享(0)

陶劲草

2008-05-14

提出了一种基于加权平均脸和二维成分分析(PCA)特征空间相结合的人脸识别算法。通过引入样本类间和类内加权平均脸,二维PCA既使得类间散布特征矩阵最大化又减小了类内样本的差异,该方法较传统PCA和

电子科技大学信号与信息处理专业

#电子、通信与自动控制技术#

0评论(0 分享(0)

Chen Jinyan

Human gait recognition aims to identify people by their walking style. In this paper a difference image based human gait identification method is proposed. For each human gait images sequence, gauss model based background estimation is used to segment frames of the sequence to obtain the silhouette images with less noise. By comparing the difference of two adjacent silhouettes in the images sequence, we can get a difference images sequence. Every difference image in the difference sequence indicates the body moving feature during ones walking. By projecting every difference image to Y axis or X axis we can get two feature vectors. Project every difference images of the whole walking images in one walking cycle we can get two matrixes. These two matrixes indicate the style of ones walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform the above matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. Experimental results on a gait database of 124 people show that the rank 5 identification accuracy can achieve 92%.

2014-01-24

School of Computer Software Tianjin University

#Computer Science and Technology#

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