搜索资源列表
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1下载：
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
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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
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this program implement a pca_svm face recognition
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this code implements a svm face recognition
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ASV CODE FOR FACE RECOGNITION
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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
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This program with kpca, PLS, SVM to achieve face recognition, the facial expression distinguish effect is obvious, the resolution is ninety-four percent
-This program with kpca, PLS, SVM to achieve face recognition, the facial expression distinguis
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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
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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
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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
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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
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this paper gives a brief discr iption of different methodology for face detection and facial expresssion recognition.for face detection Exhaustive search,Branch and Bound,Viola-Jones methods can be used. for expression recognition gabor filter, discr
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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 !
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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
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Face recognition written in MATLAB. This code implements Fisher s Discriminant Analysis and SVMs using LIBSVM.-The motivation of this project is to implement several techniques for face recognition:
Principal Component Analysis
Fisher’s Linear
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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
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relize the idea of the face recognition of PCA-SVM
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Face recognition Using SVM (Support Vector Machine)
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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)
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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)
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