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找出人脸，会把眼睛，鼻子，用红线圈起来，用C++与OPenCV结合实现。-Identify the human face, will be the eyes, nose, with red coils, use C++ and realize OPenCV combination.
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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
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Eigenfaces: PCA tends to find a p-dimensional subspace
whose basis vectors correspond to the maximum
variance direction in the original image space (p N).
We called the new subspace defined by basis vectors “face
space”. First, all training
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Eigenfaces: PCA tends to find a p-dimensional subspace
whose basis vectors correspond to the maximum
variance direction in the original image space (p N).
We called the new subspace defined by basis vectors “face
space”. First, all training
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对人脸图像库的训练素材进行主成分分析，从而识别人脸图像。较详细说明见程序内部。-Face image database on the training material for the principal component analysis to identify the face image. See more details within the program.
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利用训练标准，利用PCA进行人脸识别，其中利用奇异值定理和能量选择来进行识别空间重构。-Use of training standards, the use of PCA for face recognition, including the use of singular value theorem and the energy of choice to identify space reconstruction.
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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 su
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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 已通过测试。
-Good performance, performance in the ability to learn the use of support vector machines based on PSO training SVM face recognition combined
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用matlab实现的基于马尔科夫模型和支持向量机的人脸识别系统。非原创，运行了效果很好，功能很强大。具体功能：可根据训练与测试样本生成数据库；计算人脸识别率（96.5 ）；可以识别出指定的图像；可以识别摄像头获取的人脸图像。-Matlab based on markov model and support vector machine (SVM) face recognition system. The original, run the effect is very good, the fun
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基于opencv库中的人脸识别代码，可以实现检测并跟踪视频中的人脸，可以选择训练人脸模型，或者直接加载训练好的人脸模型来识别视频中的人脸身份。-Based opencv library, this face recognition code can be achieve detecting and tracking faces in the video. You can choose training face model, or load directly trained human face
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根据pca主程序分析的人脸识别。测试集用于训练特征脸空间，测试集是一张人脸一张动物脸，程序目的是识别出人脸与非人脸-Face recognition based on the analysis of the main pca. Test set for training Eigenface space, a test set is a human face animal face, the program aims to identify the face and non-face
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## 人脸识别GUI设计
这是我在理解PCA算法后，设计`MATLAB GUI`实现人脸识别。
### 使用方法：
1. 运行face.m主脚本
2. 点击`训练机器`选择train文件夹
3. 点击`choose photo`选择test文件夹下的一张图片
4. 最后点击`recognize`即可进行识别
5. 点击`Accuracy`可计算整个test文件夹下所有图识别准确率
###(## face recognition GUI design
This i
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实现人脸识别，标识。首先采集人脸信息，训练后保存，即可识别(Face recognition, identification. First of all, the acquisition of face information, after training to save, you can identify)
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