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PCA-facerecognize
- 利用主成分分析（ＰＣＡ）实现对人脸特征的降维，然后利用最近邻实现人脸识别-Using the main component analysis (PCA) to realize the reduction of facial features, then use the nearest neighbor to realize face recognition
isomap
- 一种流形学习算法，用于非线性降维算法，实验数据用的人脸数据。(A manifold learning algorithm for nonlinear dimensionality reduction algorithms, using face data for experimental data.)
pca_face
- 利用pca方法对人脸数据进行降维并显示降维结果(The PCA method is used to reduce the dimensionality of the face data and show the results of dimensionality reduction)
FaceRecognition
- 利用pcat提取特征值并完成降维，进而通过测试一张图片到特征脸的三阶距离完成人脸识别 言语表达不清的地方请见谅咯(we used the pca to make a facerecognition.)
PCA
- 非常经典的特征提取算法，经常用来做降维方法，但是也可以直接用来做特征提取，很适合图像处理入门，在人脸识别也经常用到(Very classic feature extraction algorithm, often used to do dimensionality reduction methods, but can also be used directly to do feature extraction, it is suitable for image processing, in fa
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- 基于gabor变换和pca降维的人脸识别算法，具有较高的识别率(Face recognition algorithm based on Gabor transform and PCA dimension reduction, with high recognition rate)