Description: 现有的代数特征的抽取方法绝大多数采用一维的方法，即首先将图像转换为一维向量，再用主分量分析（PCA）,Fisher线性鉴别分析（LDA）,Fisherfaces式核主分量分析（KPCA）等方法抽取特征，然后用适合的分类器分类。针对一维方法维数过高，计算量大，协方差矩阵常常是奇异矩阵等不足，提出了二维的图像特征抽取方法，计算量小，协方差矩阵一般是可逆的，且识别率较高。-existing algebra feature extraction method using a majority of the peacekeepers, First images will be converted into one-dimensional vector, and then principal component analysis (PCA), Fisher Linear Discriminant Analysis (LDA), Fisherfaces audits principal component analysis (KPCA), and other selected characteristics, then use the appropriate classification for classification. Victoria against an excessive dimension method, calculation, covariance matrix is often inadequate singular matrix, a two-dimensional image feature extraction method, a small amount of covariance matrix is usually reversible, and the recognition rate higher. Platform: |
Size: 2048 |
Author:小弟 |
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Description: 最经典的人脸识别中的fisherface代码，在此之前要对特征空间降维，通常采用PCA降维，此代码基于降维实现类间与类内比值的最大化。-The most classic Face Recognition fisherface code, in this feature space prior to dimensionality reduction, PCA dimensionality reduction is usually used, this code-based dimensionality reduction to achieve between-class and category to maximize the ratio. Platform: |
Size: 1024 |
Author:heying |
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Description: 人脸识别的经典算法的完美结合，PAC与FISHER算法C++实现，首先通过PCA进行维数约简，然后通过FISHER进行最有利的方向投影。识别效率是所有监督学习的上限。-Face Recognition Algorithm for the perfect combination of classic, PAC and FISHER algorithm C++ Realize, first of all carried out through the PCA dimension reduction, and then through to the most favorable FISHER projection direction. Recognition efficiency is all supervised learning ceiling. Platform: |
Size: 758784 |
Author:NEO |
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Description: 文档中包括两个文件：分别是pca人脸识别分析以及fisher人脸识别分析。文中代码包括详细的注释，读者一旦下载很快就可以上手！代码中的相关理论可以参考Dota的《模式分类》一书！- The archive consists of two documents: PCA face recognition and Fisher face recognition analysis. Text codes include detailed notes, readers will soon be able to comprehend it, once started! The relataed theory can be referred to Dota s masterpiece:《pattern classification》! Platform: |
Size: 3072 |
Author:feixiaoxing |
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Description: 本程序实现了pca，fisher实现人的脸布表情的识别，很精确的分辨率，运行速度很快，具有很高的识别效果-This application implements pca, fisher realize people face cloth expressions of the recognition, very precise resolution, running fast and has high recognition effect
Platform: |
Size: 701440 |
Author:sun |
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Description: 本程序实现了fisher,贝叶斯，pca实现人的脸布表情的识别，能有效地分辨出喜怒哀乐等五种表情,结果很好-This application implements fisher, bayesian, pca realize people face cloth expressions of the recognition, can effectively distinguish laughter, anger, sorrow and happiness five expression, the result is very good Platform: |
Size: 11264 |
Author:sun |
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Description: 本程序为用pca和fisher实现人脸识别，具有很好的识别效果，识别率为90 -The procedures for the use pca and fisher realize face recognition, has the very good recognition effect, recognition rate is 90 Platform: |
Size: 1026048 |
Author: |
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Description: 本程序为用pca和fisher实现人脸识别，具有很好的识别效果，识别率为百分之八十-The procedures for the use pca and fisher realize face recognition, has the very good recognition effect, recognition rate is eighty percent Platform: |
Size: 2052096 |
Author: |
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Description: matlab平台实现人脸识别，通过PCA降维后再通过线性判别分析LDA实现人脸匹配。内附ORL人脸数据库，运行main函数即可输出结果-Matlab platform to achieve face recognition, PCA dimensionality reduction and then through linear discriminant analysis LDA face matching. Contains ORL face , run the main function to output the results Platform: |
Size: 4235264 |
Author:don |
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