搜索资源列表
PCA_ORL
- Matlab环境下，实现用PCA方法提取EigenFace,之后通过SVM方法对人脸图像进行分类识别。-Face recognition via PCA and SVM method
KPCA
- 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
CODE
- 1.GeometricContext文件是完成图片中几何方向目标分类。 参考文献《Automatic Photo Pop-up》Hoiem 2005 2 GrabCut文件是完成图像中目标交互式分割 参考文献《“GrabCut” — Interactive Foreground Extraction using Iterated Graph Cuts》 C. Rother 2004 3 HOG文件是自己编写的根据HOG特征检测行人的matlab代码 4 虹膜识别程序
gaborsvm1
- 先用gabor 小波滤波器,做特征提取，然后用支持向量机（SVM）做分类，来实现人脸检测.需要用matlab 2010 或更新的版本才能运行-the code is used for face detection.Firstly it use gabor wavelet filter for feature extraction,Secondly it use support vector machine (SVM）for classification.matlab 2010 required.
face-recognition
- 一个有关人脸识别的程序，是PCA和SVM的，可以运行-a code about face recognition
pacVsm
- pca + svm人脸识别代码 图片目录需要自己修改-the pca+ svm Face Recognition code picture directory need to modify
matlab-face-detection
- pca+svm 与pca +adaboost 人脸检测，里面包含有程序的详细说明-pca+svm, pca+adaboost people face detection, which contains a detailed descr iption of the program
svm.zip
- 基于支持向量机的人脸年龄估计matlab仿真。,Face Age estimated based on support vector machine matlab simulation.
chapter13
- matlab实现PCA和SVM人脸识别 主成分分析 和 支持向量机-the matlab realize PCA and SVM face recognition
face
- 本程序是运用SVM来实现人脸识别算法，能直接运行且能进行二次开发-This procedure is to use SVM to implement face recognition algorithm that can run directly and can perform a secondary development
face
- Matlab PCA+SVM人脸识别,通过PCA和SVM算法达到人脸识别的功能。-Matlab PCA+SVM，To identify people s face.
svm_matlab_facerecognition
- 利用PCA算法进行特征提取和数据降维，再用SVM算法进行人脸识别的程序，里面有人脸数据库！-Use PCA algorithm for feature extraction and data reduction, and then SVM algorithm recognition program, which was face !
biaoqingshibie
- 是对jaffe人脸库进行识别测试的主程序，将jaffe人脸库分为训练集和测试集两部分，首先对图片进行LBP+LPQ特征提取，然后svm分类识别，统计识别率 -Is jaffe face recognition test the main library, the library will jaffe face divided into training and test sets of two parts, the first of LBP+LPQ image feature extrac
svm
- 利用matlab实现svm函数包的调用，在人脸数据库yale上进行人脸识别-using matlab to apply function svm to achive scan face on the data of yale
基于主分量的人脸重构
- 本实验是基于主成分分析法（PCA）在人脸识别中的应用，采用SVM分类器在ORL人脸库的基础上通过Matlab实现了快速PCA算法的验证仿真。
(PCA+SVM)人脸识别
- 人脸识别，降维 加分类，主成分分析降维，支持向量机分类(Face recognition, principal component analysis reduced Vega classification, dimension reduction, support vector machine classification)
PCA+SVM
- 采用经典的ORL人脸数据集，利用PCA进行进行降维，然后用SVM进行数据集的分类和训练。上传文件内包含libSVM3.2安装包(The classical ORL face dataset is used for dimension reduction by PCA, and then SVM is used to classify and train the dataset.)
贝叶斯人脸识别
- Pattern-Recognition-and-Machine-Learning-master,项目包括使用贝叶斯分类器的字符识别，基于GMM的图像分割，使用PCA的人脸识别和具有径向基函数的多类SVM分类器(Pattern-Recognition-and-Machine-Learning-master)
PCA+SVM的人脸识别
- 使用pca和svm的方法对人脸进行识别和检测，最终达到人脸识别的功能(Face recognition and detection using PCA and SVM methods, and finally achieve the function of face recognition)
基于PCA和SVM的人脸识别系统
- 先通过图像处理提取人脸的各个特征，然后对人脸通过PCA进行降维，然后通过SVM进行人脸识别(Firstly, the features of human face are extracted by image processing, then the dimension of human face is reduced by PCA, and then the face is recognized by SVM)