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通过分类器自动识别图像中的人脸-Automatic recognition through classifier human face images
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用OPENCV做的人脸识别程序，实现跟踪检测，用的是自带的分类器-OPENCV do with face recognition program, to achieve tracking and detection, using a built-in classifier
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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
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用haar 小波分类器分析人脸识别 的源码。分级强分类器-Haar wavelet classifier with the source code of face recognition. Rating strong classifier
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我们使用MATLAB软件实现了人脸识别并统计其识别率。本实验采用PCA（主成分分析）方法，利用K-L变换和奇异值分解原理实现。并分别采用最近邻法分类器得出它们的成功率。-We use face recognition software and the MATLAB Statistics recognition rate. The present study, PCA (principal component analysis) method, using KL transform and sin
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This paper investigates a new face recognition system based on an efficient design of MLP classifier using each SIFT (Scale Invariant Feature Transform) keypoint as feature.
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This paper investigates a new face recognition system based on an efficient design of classifier using SIFT (Scale
Invariant Feature Transform) feature keypoint. This proposed system takes the advantage of SIFT feature which possess strong
robust
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My presentation consists of four main parts.
At first, I will introduce some problems of face recognition techniques including general SIFT based methods
and the proposed SIFT classification method to solve the problem.
And then the propo
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SVM分类器，可用于人脸识别，机器学习等。-Texture feature extraction, and classification, SVM classifier is.Can be used for face recognition, machine learning, etc.
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用FLD分类器实现人脸分类，里面包含20张训练图片和十张测试图片-FLD classifier face classification, which contains 20 training images and 10 test pictures
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pca算法实现人脸识别，包括数据图片，特征提取算法，最近邻分类器算法-pca algorithm for face recognition, including data pictures, feature extraction algorithm, nearest neighbor classifier algorithms, etc.
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基于PCA和FLD的人脸识别的线性分类器-Face recognition based on PCA and FLD linear classifier
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本程序实现位图的读写，均衡化，滤波，LBP，LTP特征提取以及基于LBP，LTP和卡方距离，最近邻分类的人脸识别，批量给图片改名等功能-The program can read and write a bitmap, equalization, filtering, LBP, LTP feature extraction and nearest neighbor classifier for face recognition based on LBP, LTP and chi-square d
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DK-SVD，CVPR文章 Discriminative K-SVD dictionary learning for face recognition 源码，效果好于原始SRC-DK-SVD，the source code of CVPR paper Discriminative K-SVD dictionary learning for face recognition, its has a better performance than the classical SRC classifie
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基于特征向量的人脸识别，有训练集和样本集，通过Adaboost强分类器算法实现，结果精确度达到95 以上，给定一个example,就可以在样本集中识别出对应的人脸。-Face recognition based on feature vectors have the training set and sample set by Adaboost strong classifier algorithm, the results of more than 95 accuracy, given an
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基于opencv3.0的非线性SVM分类器源码（可直接运行），在人脸识别类的领域。-Based on nonlinear SVM classifier opencv3.0 source (can be run directly), in face recognition field.
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通过奇异值分解作为特征处理，训练人脸识别分类器，附带测试图片(Singular value decomposition (SVD) is used as feature processing to train the face recognition classifier)
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本程序为人脸识别系统，首先建立人脸库模块，然后对人脸库进行信息编辑以及训练人脸识别分类器，最后为人脸识别模块。采用的visual studio + opencv实现，界面清晰美观，实验效果较好。(The program for the face recognition system, the first establishment of the face library module, and then face the library for information editing and t
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主要功能为脸部识别，有相关分类器标记特征点之间的距离(The main function is face recognition, and the distance between feature points with related classifier marks.)
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人脸识别系统 通过matlab自带分类器和降噪功能对图片人脸的五官和人脸进行勾勒(The face recognition system is based on Matlab's own classifier and noise reduction function to outline facial features and faces.)
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