搜索资源列表
LDA-based-face-recognition
- 基于LDA的人脸识别技术，从ORL数据库读数据，然后从中取一部分进行训练，一部分进行测试。-This code is LDA base face recognition programme. It reads nots faces from ORL database and the rest (noc-nots) are used as test. LDA_Performance shows the recognition performance.
lda_orl
- This code is LDA base face recognition programme. It reads nots faces from ORL database and the rest (noc-nots) are used as test.LDA_Performance shows the recognition performance. -This code is LDA base face recognition programme. It reads nots f
shibie
- 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
lda
- This code is LDA base face recognition programme. It reads nots faces from ORL database a
ORL
- 人脸库，一共40个脸，每个脸10张图片，.pgm格式，可以用matlab直接处理-Face database, a total of 40 faces, each face 10 pictures,. Pgm format, you can deal directly with matlab
FinalProject_rc2748
- This my course final project for biometrics. It implements a robust face recognition system. Techniques used include Log-Gabor filter , Kernel Discriminant Analysis(KDA) and Sparse Representation . Test data included(ORL database of faces).-This is m
fisherRec
- Face recognition using fisher faces method with the ORL database
FastPCA_Feature_extraction-on-ORL
- 通过FastPCA在ORL人脸数据集上提取主成分脸并可视化，ReadFaces函数读取每个人的前五张图片作为实验数据集。-Extracting principal component faces on ORL_faces datasets by FastPCA and visualing them are done.ReadFaces function reads the five pictures of everyone as the experimental data set.
chapter13
- pca,svm人脸识别,有训练，识别，和orl人脸库-pca,svm source code, can detect human faces
ORL-faces
- ORL人脸数据库，主要用于人脸识别和人脸检测的研究-ORL face database, mainly used to study face recognition and face detection
PCA_Face_Recognition
- 这是基本面识别的PCA程序代码。它写道nots（这里面5）从数据库（NOC - nots and the rest）are used as测试。PCA的性能_节目the识别性能。-This code is PCA base face recognition programme. It reads nots(here 5) faces ORL and the rest (noc-nots) are used as test. PCA_Performance shows the recognit
piliang
- 这是批量读取ORL人脸库的人脸 再进行批量处理 最后再批量保存的程序 自己运行过 可以实现-The function is meant to read, do with and save ORL faces once a time.
faceRecognition
- 基于SVM和PCA的人脸识别，使用了ORL人脸数据集和libsvm.jar-Face recognition based on SVM and PCA. ORL faces dataset and libsvm.jar are used
PCA
- 数据来源：ORL Database of Faces人脸数据库 其中同一个人的10张人脸图像为一组，共40组,图像大小为112x92 采用PCA算法实现对人脸的识别，当每组训练样本占70 时，识别准确率达到96.67 -Source: ORL Database of Faces face in which the same person 10 face images as a group, a total of 40 groups, image size of 112x92 using
PCA人脸识别
- 采用PCA算法对ORL Database of Faces人脸数据库(15个人，每人10幅图像，样本数量15*10)进行识别，通过改变每类训练样本中的比例，在默认累计率情况下，可得到不同的识别准确率
mpca
- 以下Matlab项目包含用于模块化pca的源代码和Matlab示例。 代码有一些问题，orl面部从1.pgm命名为400.pgm.5从每个类中随机抽取的测试和训练集。图像分为4部分。-The following Matlab project contains the source code and Matlab examples used for modular pca. the code has some problem,orl faces are named 1.pgm to 400.pg