搜索资源列表
eigenfaces
- 基于SVD的主量提取的人脸识别的matlab源码-based on the SVD Major Face recognition from the Matlab FOSS
PCA_Program
- 完全按照论文Face Recogniton Using Eigenfaces设计的PCA源码，无解压密码-in full accordance with the thesis Face Recogniton located Using Eigenfaces PCA of source code, without extracting passwords
Eigen_Fisher
- Tutorial to understans EigenFaces & FisherFaces. It has pseudo code for Matlab implementation of Eigenfaces & FisherFaces
1
- Amir Hossein Omidvarnia用matlab编写的基于PCA的人脸识别系统和基于FLD的人脸识别系统,其中 的图像示例为Essex face database中 face94 的部分图像,文献可参考"Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection."已经测试过程序可正常运行没有问题。-Amir Hossein Omidvarnia prepared using
pcaAlgorithm
- MATLAB code for generating faces using PCA. Displays all of the eigenfaces in a separate figure.
findSimilar3.m.tar
- find similar faces with eigenfaces.
Eigenfaces
- Eigenfaces tests for grayscale images using PCA and SVD
CalculateRate
- 用matlab编写的基于人脸识别系统,文献可参考"Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection."已经测试过程序可正常运行没有问题-Prepared using matlab face recognition system based on the literature may refer to " Eigenfaces vs. Fisherfaces: Recognition
altroeigen
- These file contains an implementation of eigenfaces for MAtlab
altroeigen2
- eigenfaces algorithm
fisherface
- 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
FaceRecognition
- Face Recognition based on PLE dataset from CMU-Using Eigenfaces and Template matching
Eigenfaces_for_Recognition_kimo
- Eigenfaces for Recognition
facerecognition-eigenfaces
- Face Recognition with eigenfaces
EigenFace
- 基于PCA的人脸表情识别，可以辨别高兴，愤怒和厌恶三种表情。 -In this project, Eigenfaces are used to classify facial expression. It has been assumed that, facial expression can be classified into some discreet classes (like anger, happiness, disgust or sadness) whereas: 1. A
mypca
- principal component analysis (PCA ) is a well known approach for dimensionality reduction of the feature space. It has been successfully applied in face recognition. The main idea is to decompose face images into a small set of feature images called
pca
- pca进行人脸识别的原理和代码，特征脸方法，图像重建-PCA for face recognition principle and code, Eigenfaces method, image reconstruction
Eigenfaces
- eigenfaces descr iption for face recognition
eigenfaces
- eigenfaces的代码仿真及其实现，实现人脸识别系统-the eigenfaces code simulation and its implementation to achieve a face recognition system
Untitled Folder
- Eigenfaces in face detection