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在本设计中源于将图像看作随机场的实例,同时从信号处理的观点出发,对图像进行统计描述。通过K-L变换降低人脸特征的维数,提取人脸图像的代数特征,并排序。这样,利用代数特征的比较,可从人脸库中识别一幅人脸。-in the design of the images from the airport as with the examples, from the viewpoint of signal processing, right image descr iptive statistics. Thr
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Matlab脸部识别程序包括
haar feature
adaboosting,Matlab including facial recognition program haar featureadaboosting
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人脸识别提出的LBP特征计算程序,简单实用的特征,可以得到统计的直方图特征,LBP features of face recognition proposed by the calculation procedure, simple and practical features of the histogram statistics can be characteristic of
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对含有人脸面部特征进行提取,可以有效的提取出人脸的面部信息,并且进行保存,同时,还有对话框界面-With the Department of Human face features extraction, the extract can effectively face the face of information, and save at the same time, have the dialog box interface
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在matlab中,检测出人脸,该文件包括文章和代码-FACE DETECTION USING LOCAL SMQT FEATURES AND SPLIT UP SNOWCLASSIFIER
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基于小波变换的matlab图像处理程序,可用于图像预处理,人脸识别,特整提取等功能。-Based on wavelet transform matlab image processing procedures, can be used for image preprocessing, face recognition, special features such as the whole extract.
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this a source codes for face recognition using local features
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人脸识别MATLAB工具箱
Faces detection toolbox v 0.1 -This toolbox provides some tools for faces detection using Local Binary Patterns and Haar features.
The task of detection is done by boosting approaches such Adaboosting, FastAdaboosting and Gentleboos
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结合人脸肤色和发色进行的人脸检测,可以忽略人脸的姿态表情,不用进行人脸特征的定位-Combination of face color and hair color for face detection, facial gesture can ignore the expression, do not carry out the positioning of facial features
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摘要:主成分分析(PCA)的人脸识别算法,以减少的特征向量是涉及到对抽象的特点,改进了主成分分析(一)iUumination算法的变化影响酶原sed.The方法是基于上减低与正常化其相应的标准差的特征向量元素相关联的大特征值的特征向量的影响力的想法。耶鲁大学和耶鲁大学面临的数据库面对数据库B是用来验证-Abstract:In principal component analysis(PCA)algorithms for face recognition,to reduce the influen
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High information redundancy and correlation in face images result in efficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of t
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计算机人脸识别技术( Face Reocgnition)就利用计算机分析人脸图像,从中提取出有效的识别信息,用来辨认身份的一门技术。[ 1 ]即对已知人脸进行标准化处理后,通过某种方法和数据库中的人脸样本进行匹配,寻找库中对应人脸及该人脸相关信息。人脸自动识别系统有两个主要技术环节,一是人脸定位,即从输入图像中找到人脸存在的位置,将人脸从背景中分割出来,二是对标准化后的人脸图像进行特征提取和识别。本文中介绍的PCA (特征脸)方法就是一种常用的人脸
特征提取方法。-Computer Fac
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实现人脸特征定位及人脸描述符提取功能。很好很强大。-
To get started, run "demo". This detects faces in the example
image, loading cached detections from files if available,
localizes the facial features and extracts descr iptors for each
face.
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程序实现了基于Gabor特征和PCA的人脸识别算法,具有较好的识别效果。-Program for Gabor features and PCA-based face recognition algorithm has better recognition effect.
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利用Gabor特征进行人脸识别的论文与matlab实现算法,比较新,感觉还不错。-Face recognition using Gabor features papers and matlab algorithm, a relatively new, I feel pretty good.
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一个用Java做的人脸识别程序,
功能比较强大,大家可以做个参考-A face recognition program to use Java to do, features more powerful, we can be a reference
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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/matlabce
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运用HOG提取人脸特征与支持向量机算法训练模型,进行人脸识别(Using HOG to extract facial features and support vector machine algorithm training model for face recognition)
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可以打开视频文件,对视频文件中的人头进行检测并统计数量。算法有HOG RCNN 及Aggrate Channel Features三种(You can open the video file, the head of the video file to detect and statistics. Algorithm HOG RCNN Aggrate Channel Features tionchannel three)
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使用pca方法对图像进行特征提取,对训练集的20个人的共一百张人脸进行训练,使用adaboost算法生成强分类器,可以对测试集的人脸图片进行识别,且识别率较高(The PCA method is used to extract the features of the image, and the training is carried out for a total of 100 faces of 20 people in the training set. The AdaBoost algor
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