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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.
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Size: 4894720 |
Author: 陈其星 |
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Description: 用帧间差法及Adaboost算法实现人脸检测，可以增加人脸检测的效率-Using inter-frame difference method and the Adaboost face detection algorithm, it can increase the efficiency of face detection
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Size: 2004992 |
Author: 萧枫 |
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Description: 基于模板匹配与支持矢量机的人脸检测
梁路宏 艾海舟 肖习攀 叶航军 徐光佑 张钹
。本文提出了一种将模板匹配与支持矢量机（SVM）相结合的人脸检测算法。算法首先使用双眼—人脸模板对进行粗筛选，然后使用SVM分类器进行分类。在模板匹配限定的子空间内采用“自举”方法收集“非人脸”样本训练SVM，有效地降低了训练的难度。实验结果的对比数据表明，该算法是十分有效的。-Based on template matching and support vector machine Face Detection Liang Wang Ai Haizhou Road, Xi Pan Xiao Ye Zhang Bo Xu Guangyou military aircraft. This paper proposes a template matching and support vector machine (SVM) a combination of face detection algorithm. Algorithm the first to use both eyes- face template to carry out coarse filter, and then use the SVM classifier to classify. Template matching in the sub-space limit the use of
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Size: 1135616 |
Author: cy |
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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
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Size: 27648 |
Author: 杨愚根 |
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Description: 图像分类器，可实现贝叶斯滤波以及分类，应用与人脸识别，车牌识别等等。-Image classifier, Bayesian filtering can be achieved as well as the classification, application and face recognition, license plate recognition and so on.
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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)
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Size: 977920 |
Author: 严锐 |
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Description: 人脸检测程序,使用Adaboost算法训练的分类器，分类效果良好
OpenCV平台-Face detection procedures, the use of Adaboost classifier training algorithm, classification results OpenCV platform
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Size: 2048 |
Author: Neo |
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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)
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Size: 1326080 |
Author: 张晓 |
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Description: 一个典型的人脸识别系统主要包括训练过程和识别过程。训练过程主要完成将已知人脸进行定位、特征提取与选择、以及分类器的设计；识别过程则完成将未知图片进行处理，并最终识别出身份的分类和决策-A typical face recognition system mainly include the training process and the identification process. Completion of the training process will be the main face of known position, feature extraction and selection, and classifier design identification process will be completed to deal with the unknown image, and ultimately identify the identity of the classification and decision-making
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Author: likunbao |
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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
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Author: 王云 |
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Description: 本文的目的是借助Paul Viola最新提出的实时特征检测的技术，实现一个能够进行快速人脸检测的系统。并且通过训练，得到尽可能优化的分类器构造参数，从而获得具有高检测速度和检测正确率的人脸检测系统。-The purpose of this paper by drawing on the latest proposed by Paul Viola real-time feature detection technology, to realize a fast face detection system. Through training, to be as much as possible to optimize the classifier structure parameters to obtain a high detection speed and detection rate of correct face detection system.
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Size: 3033088 |
Author: 王峰 |
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Description: 人脸识别中2DPCA算法的matlab程序，使用最近邻分类器进行识别。-Face Recognition 2DPCA algorithm matlab procedures, the use of nearest neighbor classifier to identify.
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Size: 1024 |
Author: niushaobo |
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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.
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Size: 896000 |
Author: kq |
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Description: 人脸识别程序，采用的是knn分类器，基于类内类间距离准则，特征提取。-Face recognition process, using the knn classifier, based on within-class inter-class distance criteria, feature extraction.
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Size: 14336 |
Author: wasd |
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Description: Face Detection using local SMQT features and split up SnoW classifier
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Size: 3454976 |
Author: heyudi |
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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.
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Size: 1397760 |
Author: 霞 |
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Description: 应用OpenCV的人脸识别，基于haar like cascade classifier-openCV face detection tutorial
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Size: 11104256 |
Author: kevin |
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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
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Size: 9036800 |
Author: 钟佩 |
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Description: 人工智能机器学习入门 简易的人脸识别程序-face classifier
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Size: 5120 |
Author: lix |
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Description: face detection using harcascade classifier
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Size: 11264 |
Author: huma443
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