搜索资源列表
Yale_PCASVM
- 在Yale 人脸库上运用PCA＋SVM的方法实现了人脸检测，并统计识别率
FaceRec
- 基于matlab2008的人脸识别系统，使用了PCA +Adaboost与PCA+SVM分别实现了人脸识别，使用了orl人脸库，给一个人的图片就可以识别此人身份，识别率高达84 -Matlab2008 face recognition system based on use of the PCA + Adaboost achieved with the PCA+ SVM face recognition, respectively, using the orl face database
kpca
- 使用核PcA来识别图片，图片为200张测试图片，200张训练图片，包含在在压缩文件中。-To identify the use of nuclear PcA picture, pictures, for 200 test images, 200 training images, is included in the compressed file.
FaceRecEvaluator
- 人脸识别算法matlab代码，可以实现，如PCA,ICA，SVM,LDA等-Matlab code for face recognition algorithms can be achieved, such as PCA, ICA, the SVM, LDA
pca-svm
- 基于pca的人脸识别程序，人脸库需要自己下载，供参考-Pca-based face recognition program needs to download face database, for reference
gabor-pca
- 本程序是先用gabor小波变换对人脸图像处理，然后在用pca进行降维，最后用svm分类器进行多分类分类识别，包扩完整的orl人脸库，需注意的是，svm工具箱是用的libsvm工具箱，运行前先配置好libsvm。版本号：libsvm-mat-2[1].89-3[FarutoUltimate3.0]-This procedure is to use the human face gabor wavelet transform image processing, and then to reduce
PCA-and-SVM-Face-recognition
- 采用PCA对人脸特征进行抽取，用SVM多累分类器对人脸进行识别，有操作界面-Using PCA for facial feature extraction, and more tired with the SVM classifier for face identification, a user interface
5
- 本程序实现了用pca,svm实现人脸表情的识别，很精确的结果，具有很高的识别效果-This application implements with pca, SVM realize the recognition face expression, very accurate results, has the very high recognition result
7
- 本程序实现了用pca以及kpca,svm实现人脸表情的识别，很精确的结果，具有很高的识别效果-This application implements with pca and kpca, SVM realize the recognition face expression, very accurate results, has the very high recognition result
8
- 本程序实现了用pca以及贝叶斯,svm实现人脸表情的识别，很精确的结果，具有很高的识别效果-This application implements with pca and the bayesian, SVM realize the recognition face expression, very accurate results, has the very high recognition result
FaceRec
- 人脸识别系统 PCA降维， SVM 分类， 40*10人脸数据库 对机器视觉 智能识别有帮助 -face recognition
PCA_ORL
- 基于PCA和SVM的人脸识别系统的实现，实验数据采用ORL人脸库。-Based on the PCA and the SVM face recognition system is realized, the experiment data using ORL face database.
FaceRec
- 利用SVM和PCA结合的方法进行的人脸识别实验，希望对于初学模式识别的人有所帮助-Face recognition experiments using SVM and PCA methods, hoping to be helpful for beginner pattern recognition
PCAPSVM
- 使用pca+svm进行人脸识别的代码，很详细-detailed code for face recognition using pca+svm
face-recognition-system
- 基于PCA和SVM的人脸识别系统，该系统为Matlab源代码编程，利用PCA（主成分分析）和SVM（支持向量机）方法进行训练、识别和测试，人脸识别率为91 。-Based on the PCA and SVM of the face recognition system
FaceRec_facerecognition
- 基于SVM和PCA的人脸识别算法，有GUI界面，程序运行良好。-Based on SVM and PCA face recognition algorithm, GUI interface, the program works well.
pca_svm
- PCA+svm算法进行人脸识别，识别率在百分之80~90- Face recognition algorithm Pca+ support vector machine Recognition rate of about ninety percent, interested friends can be used as a reference
FaceRec_SourceCode
- 基于PCA-SVM的人脸识别，平均识别率达83 ，是基于matlab开发的。-PCA-SVM-based face recognition, the average recognition rate of 83 , based on matlab development.
FaceRec
- 人脸表情识别matlab程序PCA+SVM算法，SVM分类-orL人脸数据库有数据有图片-Facial expression recognition matlab program PCA+SVM algorithm, SVM classification-orL face
face-Adaboost
- 用Adaboost和PCA算法实现人脸识别，用Python写的代码，根据经典的PCA和SVM算法改编(Adaboost and PCA algorithm for face recognition, code written in Python, adapted from the classic PCA and SVM algorithm)