搜索资源列表
FaceEvaluator
- A full implementation of ICA,PCA,LDA,SVM,in both orginal and incremental in model of real time learnign for face recognition.
project
- Svm based face detector code
PSO-SVMface
- 基于PSO训练SVM的人脸识别 利用支持向量机在学习能力方面表现的良好性能,结合核主元分析特征提取方法,将其应用于人脸识别中,该方法在实验中表现了良好的识别性能,为人脸识别领域提供了一条新的识别途径-PSO-based SVM for face recognition training using support vector machine learning ability in the performance of good performance, combined with KPCA
svm
- svm用于人脸识别，效果还行！matlab，可以学习！-face recognize based on svm，its nice to learn！
DetectionLibrary
- Chesnokov Yuriy写的人脸检测库，内容涵盖肤色检测、运动估计、SVM分类、PCA/LDA/ICA特征提取以及神经网络分类器等。-The article demonstrates face detection SSE optimized C++ library for color and gray scale data with skin detection, motion estimation for faster processing, small sized SVM and NN
SVMSAPPLICATION
- SVM AND ITS APPLICATION IN FACE RECOGNTION
SVMFaceRecognition
- SVM支持向量机用于人脸识别领域的经典算法，非常有用-An algorithm of SVM used to face recognition
2DLDAwiththeSVM-basedfacerecognitionalgorithm
- 二维线性鉴别分析(2DLDA)算法能有效解决线性鉴别分析(LDA)算法的“小样本”效应，支持向量机 (SVM)具有结构风险最小化的特点，将两者结合起来用于人脸识别。首先，利用小波变换获取人脸图像的低频分量，忽 略高频分量：然后，用2DLDA算法提取人脸图像低频分量的线性鉴别特征，用“一对多”的SVM 多类分类算法完成人脸 识别。基于ORL人脸数据库和Yale人脸数据库的实验结果验证了2DLDA+SVM算法应用于人脸识别的有效性。-”Small sample size”problem
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
KPC-svm
- this program implement a pca_svm face recognition
svm
- this code implements a svm face recognition
fdsvm10
- face detection using SVM on Matlab
code
- ASV CODE FOR FACE RECOGNITION
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.
svm-base-fr
- face detection + SVM in matlab
svm
- face detection for SVM,
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)