搜索资源列表
PCA_FaceRecognition
- 人脸识别算法,包括特征空间的训练,特征脸的形成-Face recognition algorithms, including the training feature space, the formation of facial features
PCA-pro
- 整个程序是基于Yale人脸数据库的PCA算法。算法主要分成三个部分。第一个部分是选择了每类图片的八张进行训练,形成基空间。第二部分是画图,主要是怎么画出特征脸,就是那个看着比较诡异的东西。可以修改数据,程序中提供了100个特征值和16个特征值的情况示例。最后一部分就是测试部分,检测命中率。效果很理想。-The whole process is based on the Yale face database PCA algorithm. Algorithm is divided into thre
face-detection
- 一个用神经网络进行人脸检测的程序,解压后运行main.m文件,之后对神经网络进行训练,需要一定的时间,耐心等待,最大400个周期,然后就可以对灰度人脸图像进行检测了。 -A neural network with a face detection program, run the main.m file after decompression, the neural network after training, take time, patience, maximum 400 cycles
MITEx-face-database
- MITE人脸库,包括人脸和非人脸样本,作为人脸检测的训练样本-MITE face database,training samples,face detection
orl-eye-database
- orl人脸库中截取出来的眼睛样本,作为疲劳检测中的人眼训练样本-orl face database from the eyes of the interception of the sample, as the fatigue test samples in the training of the human eye
face-detector
- 人脸检测的PCA算法。先利用PCA算法,将测试集在人脸空间中进行训练,得到人脸空间的基向量,再用试验图片进行试验。-PCA algorithm for face detection. First use of PCA algorithm, the test set in the face space for training, get face space basis vectors, and then test picture test.
FaceDetect_V1.3
- windows下的人脸检测的例程,适合研究人脸算法的人,包括训练实现-the windows face detection routine for researchers who face algorithm
How-to-train-their-classifier-OpenCV
- 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
PCA_based-Face-Recognition-System
- 运行成功。用于人脸识别的PCA程序,里面包含训练集和测试集,很好。-PCA_based Face Recognition System.
fdp5final
- Face Detection System 基于Gabor特征提取和人工智能的人脸检测系统源代码 使用步骤: 1. 拷贝所有文件到MATLAB工作目录下(确认已经安装了图像处理工具箱和人工智能工具箱) 2. 找到"main.m"文件 3. 命令行中运行它 4. 点击"Train Network",等待程序训练好样本 5. 点击"Test on Photos",选择一个.jpg图片,识别。 6. 等待程序检测出人脸区域
train
- 该函数的内容包括读入人脸数据、PCA降维,数据规格化以及训练多类SVM等功能。-This function covers the face read data, PCA dimensionality reduction, data normalization and multi-class SVM training and other functions.
main_2
- 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.
ICA-face-recognition
- 主要是用独立主成分分析,做人脸识别,通过训练集和测试集的比对,得出识别率-ICA face recognition
2dpca
- 主要用2D_PCA进行人脸识别,对训练集和测试集中的人脸进行比对。-2D_PCA face recognition
a3
- 人脸识别中的主成分分析方法,通过对训练集和测试集的比对匹配,来输出识别率。-Face Recognition in the principal component analysis, through the training set and test set than on the match, to output the recognition rate.
facereg
- 人脸识别 详细注释 ORL face40 一半训练 一半测试 输出识别率 -face recognition
Adboost-face-detection
- 描述了应用adboost进行人脸检测时,训练的过程-Describes the application adboost for face detection, the training process
DPCA_Program(added-detailed-notes)
- DPCA程序,人脸识别,主成分分析,我给加了详细的注释,里面有训练和测试两部分,适合初学者,-DPCA program, face recognition, principal component analysis, I give added detailed notes, there are training and testing two parts, it is suitable for beginners,
facedetectioncode
- 人脸识别。用matlab实现,涉及到神经网络方面的知识,经过训练后,能辨识出人脸-face recognition
face-recognition
- 这是用SVM做的人脸识别Matlab源代码,里面有五部分组成,1.orl人脸数据库,供程序训练、测试用2.osu_svm工具箱用于调用3.my program 主程序,里面有详尽注释4.word分析结果一份5.注意事项说明,欢迎下载-This is the Matlab program for face recogition,welcome to download it!!