搜索资源列表
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0下载：
fisher线性鉴别分析的人脸识别，在ORL库上实验，可在其他库上运行-fisher linear discriminant analysis for face recognition, in the ORL database on the test can be run on other database
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运用奇异值分解定理的PCA方法在ORL人脸库上进行人脸识别，分类器为最近邻分类器,-The use of singular value decomposition theorem of PCA method in ORL face database for face recognition, nearest neighbor classifier for the classifier,
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使用Fisher线性鉴别分析（FLDA）方法在ORL人脸数据库上进行人脸识别试验。ORL标准人脸库共包含40人，每人10幅共400幅BMP图像。-The use of Fisher linear discriminant analysis (FLDA) at Ways on ORL face database for face recognition test. Standard ORL face database contains a total of 40 people, 10 per pe
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基于fisherface的人脸图像识别，采用lda降维的方法来识别人脸图像-This package implements a well-known FLD-based face recognition
method, which is called Fisherface [1].
All functions are easy to use, as they are heavy commented.
Furtheremore, a sample scr ipt is incl
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Amir Hossein Omidvarnia用matlab编写的基于PCA的人脸识别系统和基于FLD的人脸识别系统,其中
的图像示例为Essex face database中 face94 的部分图像,文献可参考"Eigenfaces vs. Fisherfaces:
Recognition using class specific linear projection."已经测试过程序可正常运行没有问题。-Amir Hossein Omidvarnia prepared using
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The matlab codes provided here implement two algorithms multilinear principal component analysis to run the face recognition using FERET database.
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二维线性鉴别分析(2DLDA)算法能有效解决线性鉴别分析(LDA)算法的“小样本”效应，支持向量机
(SVM)具有结构风险最小化的特点，将两者结合起来用于人脸识别。首先，利用小波变换获取人脸图像的低频分量，忽
略高频分量：然后，用2DLDA算法提取人脸图像低频分量的线性鉴别特征，用“一对多”的SVM 多类分类算法完成人脸
识别。基于ORL人脸数据库和Yale人脸数据库的实验结果验证了2DLDA+SVM算法应用于人脸识别的有效性。-”Small sample size”problem
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Copy all files in Matlab current directory and type "facerec" on
Matlab command window.
First, select an input image clicking on "Select image".
Then you can
- add this image to database (click on "Add selected image to database"
- per
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基于贝叶斯人脸识别技术的matlab人脸识别程序，在ORL库上实现，也可换用别的库进行运算，只需要更改样本数量-Bayesian face recognition technology based on face recognition matlab program, implemented on ORL database can also be used for other library operations, only need to change the number of sample
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在ORL或Yale标准人脸数据库上完成模式识别任务。用PCA与基于核的PCA（KPCA）方法完成人脸图像的重构与识别试验.
-Or Yale in the ORL face database, complete the standard pattern recognition tasks. With the PCA and kernel-based PCA (KPCA) method to complete the reconstruction of face image and reco
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sparsity preserving projections (SPP)方法，根据论文《sparsity preserving projections with applications to face recognition》使用AR人脸数据库-sparsity preserving projections (SPP)method, according to the paper "sparsity preserving projections with applications t
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多尺度LBP的原代码，用于人脸识别，在orl数据库中的识别率达97 以上。-Multi- scale LBP original code, used in face recognition and the recognition rate of over 97 in orl database.
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face database for face recognition
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This is a Simple Code for Face Recognition using PCA + LDA Approach. I hve write this code for ORL Database containing 400 images of 40 persons. I have used Eigenface Algorithm for Face Recognition. Its a Very Simple Code you can easily understand it
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SVM face recognition
程序源代码
s1-s40 --------- 人脸数据库
face.m --------- 人脸识别主程序
load_database.m------载入数据函数
其他-------------LIBSVM工具箱函数
注意：LIBSVM需要手动安装，先安装编译器，再执行make.m-Source code
S1-s40-----face database
Face. M-----face recognition t
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本程序是基于ICA（独立成分分析）方法进行人脸识别，人脸库已经给出，有需要的童靴自行下载-This procedure is based on ICA (independent component analysis) method for face recognition, face database has been given, there is a need to download children' s boots
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通过主成分分析，对已有人脸库进行人脸识别，效果非常好，非常显著-Through principal component analysis, the existing face recognition, face database are effect is very good, is very significant
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基于稀疏表达的包含测试和训练人脸的数据库的鲁棒性人脸识别-Sparse expression includes testing and training human face recognition database robustness
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程序通过提取人脸图像的质心、协方差、偏转角等特征量与数据库中已有参数进行比对，从而进行人脸的识别。-Procedure to extract the centroid of the face image, covariance, the deflection angle has the feature quantity parameters of the database and compared to identify human faces.
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Face recognition with database.
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