Description: 程序结构
整个工程可以分为3个部分：算法、功能和应用。
算法部分
算法部分目前分为4个模块：人脸对齐、光照归一化、特征提取和选择、子空间降维，每个模块是一个项目，每个项目生成一个dll供功能部分显式调用。
功能部分
功能部分只有一个项目FaceMngr，该部分依赖于算法部分，实现人脸注册、训练、识别、导入/导出等具体功能。该项目生成一个dll供应用部分隐式调用。
应用部分
人脸识别Demo.
另外，工程中还有一个项目tools，实现了一些整个工程都可能用到的函数，大部分与OpenCV有关。该项目生成一个dll供各部分隐式调用。-Program Structure
The whole project can be divided into three parts: the algorithm, function and application.
algorithm part
Algorithm is part of the currently divided into four modules: face alignment, illumination normalization, feature extraction and selection, reduced subspace
Dimension, each module is a project, each project generates a dll explicitly call for the functional part.
Features section
Functional part of only one project FaceMngr, part of the part depends on the algorithm to achieve face up, training,
Recognition, import/export and other specific functions. The project generates a dll for the supply of part of the implicit call.
Application Part
Face Recognition Demo.
In addition, there is a project engineering tools, to achieve a number of projects are likely to use the function, the majority
With OpenCV related. The project generates a dll called implicitly for each part. Platform: |
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Author:吴嘉晔 |
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Description: ：本文较为系统地介绍了纸币面值数字图象识别的计算机仿真。文中详细介绍了模版
匹配、特征点匹配、神经网络等字符识别方法，并进行了比较。根据本文研究对象的特点，选择
了从分析数字本身的拓扑结构入手，根据字符投影分布的规律来判断和识别的方法，成功实现
了纸币面值的识别。-: This article notes a more systematic introduction to digital image recognition, face value of the computer simulation. Described in detail template matching, feature matching, neural network character recognition method and compared. According to this study the characteristics of the object, select the number from the analysis of the topology of their start, the law of distribution according to the character projection to determine and identify the method successfully identified the nominal value of paper money. Platform: |
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Author: |
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Description: 此程序为根据人脸特征点识别人脸程序，实现面部图像的配准，仅作为参考-This procedure is based on facial feature points of face recognition program, to achieve facial image registration, only as a reference Platform: |
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Author:hourui |
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Description: matlab图像特征识别。分类器的训练方法。很好的学习资料。如何用OpenCV训练自己的分类器。内含人脸库共训练器使用-matlab image feature recognition. Classifier training methods. Good learning materials. How to use OpenCV train their own classification. Training face database containing a total of uses Platform: |
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Author:yanhao |
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Description: 人脸表情识别，包括提取特征点与识别，文件中有说明-Facial expression recognition, including the extraction of feature points and recognition, the document is described Platform: |
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Author:ljm |
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Description: The Principal Component Analysis (PCA) is one of the most successful techniques that have
been used in image recognition and compression. PCA is a statistical method under the broad
title of factor analysis. The purpose of PCA is to reduce the large dimensionality of the data
space (observed variables) to the smaller intrinsic dimensionality of feature space (independent
variables), which are needed to describe the data economically. This is the case when there is a
strong correlation between observed variables. Platform: |
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Author:ayoob |
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Description: 人脸识别，人脸图像预处理；读入人脸库，训练形成特征子空间；把训练图像和测试图像投影到上一步骤中得到的子空间上；选择一定 的距离函数进行识别。-Recognition, face image preprocessing read into the face database, training the formation of the feature sub-space the training images and test images were projected into the subspace obtained in the previous step select a certain distance function to identify. Platform: |
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Description: 基于主成分分析的人脸(pca)的人脸图像特征提取和识别，文件内有图库和程序。直接运行就可以了。-Based on principal component analysis (pca) face of face image feature extraction and recognition, there were atlas and program files. Run directly.
Platform: |
Size: 374784 |
Author:殷睿 |
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Description: 利用主成分分析的特征子空间进行人脸特征提取，通过人脸重建进行人脸识别-Feature subspace using principal component analysis for facial feature extraction for face recognition, face reconstruction Platform: |
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Author:孙旭光 |
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Description: 用2DPCA提取人脸特征，然后用支持向量机分类识别。效果不错。-With 2 DPCA face feature extraction, and then by support vector machines (SVM) classification and recognition. The result is right.
Platform: |
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Author:huanli |
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Description: 參考文獻「Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary」and matlab code.-「Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary」and matlab code. Platform: |
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Description: 改进PCA算法,有效地加大了人脸特征参数与其平均值间的散布程度,大大提高人脸特征参数的代表性-Improved PCA algorithm, effectively increase the distribution between the facial feature parameters and their average, greatly enhance the representation of facial feature parameters Platform: |
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Author:谭立国 |
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Description: 此代码是人脸识别定位,捕捉人脸特征,C源代码,精确度高。-Face recognition This code is positioned to capture facial feature, the C source code, and high accuracy. Platform: |
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Author:杨过 |
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Search - face feature recognition