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
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
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
- 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 !
All-Files
- 用MATLAB实现基于主成分分析（PCA）和支持向量机（SVM）的人脸识别系统，打开运行FR_GUI函数即可，我放在E盘中的，注意一下路径，当前识别率一般，也欢迎交流指正1127851044@qq.com，谢谢。-Using MATLAB analysis (PCA) based on principal component analysis and support vector machine (SVM) face recognition system to open the run FR_G
PCA_SVM face recognition
- relize the idea of the face recognition of PCA-SVM
(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.)
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)