Description: 这是MIT人脸库，包括两组，一组人脸库，一组非人脸库，可以用分类器训练，然后用人脸识别程序识别，可以不用购买人脸库了。。。不错的-Face arsenal, including two groups, one group of people to face basement, a group inhuman face, you can use the classifier training, and then use face recognition procedures for identification and can be purchased for the face. . . Good. Platform: |
Size: 4894720 |
Author:陈其星 |
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Description: 笔者自行编写的Matlab环境下的人脸识别算法小实验，
采用的是经典的PCA算法，主要内容是采用SVD方法提取出象素空间上的
PCA主分量特征，分类算法上仅是基于最小距离分类
-The author of the Matlab environment to prepare the face recognition algorithm under small experiment using classical PCA algorithm, the main contents of SVD method is used to extract pixel space on the PCA principal component features, the only classification algorithm is based on the minimum distance classifier Platform: |
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Author:杨愚根 |
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Description: Malic是一个完整的Linux下的人脸识别系统源代码，它是SourceForge上的一个开源项目，使用Malib实现实时处理，CSU Face Identification Evaluation System进行人脸识别。算法包括：主成份分析(principle components analysis (PCA)),a.k.a eigenfaces算法,混合主成份分析,线性判别分析(PCA+LDA),图像差分分类器(IIDC),弹性图像匹配算法(EBGM)-Malic is a complete face recognition system under the Linux source code, it is a SourceForge open source project, using real-time Malib treatment, CSU Face Identification Evaluation System for Face Recognition. Algorithms include: Principal component analysis (principle components analysis (PCA)), aka eigenfaces algorithm, mixed-principal component analysis, linear discriminant analysis (PCA+ LDA), the image difference classifier (IIDC), a flexible image matching algorithm (EBGM) Platform: |
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Author:严锐 |
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Description: 人脸识别论文：《采用Adaboost算法进行面部表情识别》《动态权值预划分实值Adaboost人脸检测算法》《改进的AdaBoost分类器在视频中的体育场景检测》-Face recognition thesis: the use of Adaboost algorithm to identify facial expressions, dynamic weight pre-classified real Adaboost face detection algorithm, Improved AdaBoost classifier of sports in the video scene detection Platform: |
Size: 520192 |
Author:王云 |
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Description: 【原创】VS2008开发，基于OpenCV的人脸检测程序
从摄像头获取图像，人脸检测后输出。
“输出”文件夹中的XML文件为分类器，可以修改代码载入不同的分类器，牛人也可制作自己的分类器。-【原创】 OpenCV-based Face Detection procedure to obtain images from the camera, after the face detection output. " Output" folder for the classification of XML documents, you can modify the code loading different classifier, cow people can also create your own classifier. Platform: |
Size: 896000 |
Author:kq |
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Description: 机遇PCA的人脸识别，包括图像读取，PCA降维以及机遇简单贝叶斯分类-PCA Face Recognition opportunities, including the image read, PCA dimensionality reduction as well as the opportunity for easy Bayesian Classifier Platform: |
Size: 3769344 |
Author:guodongyan |
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Description: 这是基于PCA的人脸识别，用MATLAB编写，包含了K-L变换，奇异值分解等方法，且采用了最小距离分类器-This is based on the PCA face recognition, using MATLAB to prepare, including the KL transform, singular value decomposition and other methods, and the use of the minimum distance classifier Platform: |
Size: 3072 |
Author:pan |
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Description: 本文设计基于DCT的人脸识别系统，首先结合当今人脸识别的背景和发展状况讨论了人脸识别的研究内容及在各方面的应用；然后研究了人脸识别进行预处理，讨论了人脸识别预处理的其他方法，分析各种方法的利弊，最后采用DCT（离散余弦变换）实现人脸图像预处理中的降维处理；接下来对人脸图像的特征提取进行了研究，简单叙述了几何特征提取和代数特征提取，同时深入研究了基于DCT和PCA变换的人脸图像特征提取，从而实现是否对人脸识别系统识别率有所提高的研究；对于分类器的选择，本文对两种分类器进行了探讨，即最近邻分类器和BP神经网络分类器，同时采用BP神经网络分类器作为本次基于DCT的人脸识别系统设计的分类器，并对BP神经网络进行分类的算法进行设计，BP神经网络具有学习功能，只要采用本系统对训练图片进行训练，就可以记下图像的相关信息，对于测试图片，就可以很准确的识别出该图片是属于哪个的。最后，本文对整个人脸识别系统设计实验进行了实验分析，实验结果表明本文采用的方法切实有效。- This is the design of the DCT-based face recognition systems. First of all, the background light of the current face recognition and face recognition to discuss the development of research in all aspects of content and applications And then studied the pretreatment of face recognition to discuss the pre-treatment of other face recognition methods,and analysis of the pros and cons of various methods, finally, the use of DCT (discrete cosine transform) image pre-processing to achieve in the face of the reduced-order processing Next on the face image feature extraction have been studied, A brief description of the feature extraction and algebraic geometry feature extraction, while in-depth study based on the DCT and the PCA Transform face image feature extraction in order to achieve face recognition system to identify whether the rate of increase in the research For the choice of classifier, this paper carried out on two of classifier, that is, nearest neighbor classifier and BP neura Platform: |
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Author:刘文珍 |
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Description: 基于奇异值分解的人脸识别方法
梁毅雄 龚卫国 潘英俊 李伟红 刘嘉敏 张红梅
提出了一种将傅里叶变换和奇异值分解相结合的人脸自动识别方法.首先对人脸图像进行傅里叶变换,得到其具有位移不变特性的振幅谱表征.其次,从所有训练图像样本的振幅谱表征中给定标准脸并对其进行奇异值分解,求出标准特征矩阵,再将人脸的振幅谱表征投影到标准特征矩阵后得到的投影系数作为该人脸的模式特征.然后,对经典的最近邻分类器算法进行了改进,并采用模式特征之间的欧式距离作为相似性度量,从而完成对未知人脸的识别.采用ORL (Olivetti Research Laboratory)人脸库对本文提出的人脸识别方法进行验证,获得了100.00 的识别率.实验结果表明,本方法优于现有的基于奇异值分解的人脸识别方法,且对表情、姿态变换等具有一定的鲁棒性.
-Face recognition based on singular value decomposition method
Deliberate simultaneously Gong Weiguo Li Wei Hung Stephen Lau, Hong-Mei Zhang Ying-Jun Pan
Paper, a Fourier transform and singular value decomposition of the combination of automatic face recognition. First of all, the face image by Fourier transformation, it has the same characteristics of the displacement amplitude spectra. Secondly, all training The amplitude spectrum of the sample images given in standard face representation and its singular value decomposition, find the standard characteristic matrix, then the amplitude of spectral characterization of human faces projected onto the standard characteristic matrix of projection coefficients obtained as the face of the model features . Then, the classical nearest neighbor classifier is improved, and the use of Euclidean distance between pattern features as the similarity measure, thus completing the identification of unknown human faces. using ORL (Olivetti Research La Platform: |
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Author:houhj |
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Description: 一篇很不错的关于人脸表情识别的论文。论文提出了一种基于人脸局部特征的表情识别方法，先选取人脸重要的局部特征,对得到的局部特征进行主成分分析,然后用支持向量机( SVM)设计局部特征分类器来确定测试表情图像中局部特征,同时设计支持向量机( SVM)表情分类器,确定表情图像的所属类别。-A very good facial expression recognition on paper. This paper proposes a feature based on local expression of face recognition, face first select the important local features, local features of the obtained principal component analysis, and support vector machine (SVM) classifier design to determine the local characteristics of test expression image local features, while design of support vector machine (SVM) classifier expression, determine the expression of the image category. Platform: |
Size: 428032 |
Author:王二 |
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Description: 贝叶斯分类器的设计与实现，非常好的应用程序，能够在其上面实现人脸识别-Bayesian classifier design and implementation of a very good application, face recognition can be achieved in the above Platform: |
Size: 8192 |
Author:盛器才 |
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Description: 此文的目的有三个：第一，当地连续均值量化变换特征是提出照明和传感器敏感操作在目标识别上。其次，注册稀疏Winnows网络分割，提出了加快原分类。最后，特点和分类相结合对于正面人脸检测任务。检测结果列
为MIT + CMU系统和BioID数据库。关于这人脸检测器，接收器操作特征曲线BioID数据库产生最好的结果公布。对于结果麻省理工学院的中央结算系统+数据库相当于国家的最先进的脸探测器。一个人脸检测算法的MATLAB版本可以从http://www.mathworks.com/matlabcentral/fileexchange/
loadFile.do？的ObjectID = 13701＆的objectType =FILE下载。
-The purpose of this paper is threefold: firstly, the local Successive
Mean Quantization Transform features are proposed for illumination
and sensor insensitive operation in object recognition. Secondly, a
split up Sparse Network of Winnows is presented to speed up the
original classifier. Finally, the features and classifier are combined
for the task of frontal face detection. Detection results are presented
for the MIT+CMU and the BioID databases. With regard to this
face detector, the Receiver Operation Characteristics curve for the
BioID database yields the best published result. The result for the
CMU+MIT database is comparable to state-of-the-art face detectors.
A Matlab version of the face detection algorithm can be downloaded
from http://www.mathworks.com/matlabcentral/fileexchange/
loadFile.do?objectId=13701&objectType=FILE. Platform: |
Size: 1397760 |
Author:霞 |
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Description: 采用PCA对人脸特征进行抽取，用SVM多累分类器对人脸进行识别，有操作界面-Using PCA for facial feature extraction, and more tired with the SVM classifier for face identification, a user interface Platform: |
Size: 9036800 |
Author:钟佩 |
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Search - face recognition classifier