搜索资源列表
PCA_LDA_Face_Verification
- PCA+LDA人脸识别,识别率高于单独PCA或LDA算法。需要matlab dimension reducation toolbox。-Face verification using PCA and LDA fusion. Better performance than single PCA or LDA algorithm. The image database is included. Matlab dimension reduction toolbox is requrired.
zuijinlinfenlei
- 我们使用MATLAB软件实现了人脸识别并统计其识别率。本实验采用PCA(主成分分析)方法,利用K-L变换和奇异值分解原理实现。并分别采用最近邻法分类器得出它们的成功率。-We use face recognition software and the MATLAB Statistics recognition rate. The present study, PCA (principal component analysis) method, using KL transform and sin
face4
- 基于神经网络的人脸识别的一种算法,给出了计算识别率的方法-Neural network-based face recognition algorithm, gives the recognition rate calculation method
Face-recognition-method
- 基于PCA 和BP 神经网络的人脸识别方法是针对 PCA 方法中存在的高维数问题和它对未训 练过的样本识别率低的缺点而提出的。该方法在预处理的基础上,利用粗糙集对 PCA 降维处理后的人脸特征进行约简,提取其中分类能力强的特征,实现在识别精度不变的情况下,有效的去除冗余信息;然后将约简后的属性输入到神经网络进行规则提取,利用神经网络非线性映射和并行处理的特点,增强对人脸图像识别的泛化能力。实验证明,使用该方法在识别率上有一定的提高-Face recognition method based
PCA人脸识别
- 采用PCA算法对ORL Database of Faces人脸数据库(15个人,每人10幅图像,样本数量15*10)进行识别,通过改变每类训练样本中的比例,在默认累计率情况下,可得到不同的识别准确率
123
- 在树莓派3b的硬件开发板上。可实现人脸检测人脸识别功能,识别率达到85%(On the raspberry pie 3B hardware development board. Face recognition, face recognition function, recognition rate of 85%)
facedetcer
- (转)人脸检测程序,能对输入图像变化之后进行人脸检测,识别率较好(face detection code with good performance)
Gabor+LBP
- 通过Gabor结合Lbp提取的特征进行人脸识别,获得很好的识别率(face recognition through gabor with lbp which can get a well ratio)
curvelet
- 用curvelet实现人脸识别,能实现很好的识别率(face recognition through curvelet)
gabor-pca
- 用gabor结合pca降维实现人脸识别,能得到较好的识别率(face recognition through gabor-pca)
fhmm1
- 可以将不同的人脸进行识别分类,使用隐马尔科夫算法实现较高的识别率(Different faces can be identified and classified, using hidden Markov algorithm to achieve higher recognition rate)
PCA_Face
- 基于pca的一种人脸识别,人脸识别用的库是英国ORL的人脸库,精确率可以达到80%(Based on pca a face recognition, face recognition library is the British ORL face database, the accuracy rate can reach 80%)
基于pca+lda+粗糙集+模糊神经网络的人脸识别
- 各种算法用于人脸识别,各个算法的识别率都不错,有lda,pca等算法(Various algorithms are used for face recognition, and the recognition rate of each algorithm is good. There are algorithms such as LDA, PCA and so on)
faceRecognization
- 本程序中,利用了LBP特征对人脸特征进行提取,并且利用SVM对提取的人脸特征进行训练和识别,其中,所用的图像处理库OpenCV2.4.9版本;通过对人脸库中的标准标本进行测试,算法识别率高达95%以上;(LBP features extract facial features, and use SVM to extract and recognize the facial features. The OpenCV2.4.9 version of the image processing libr
python_face_recog
- 基于python+opencv 的 人脸识别,对一段视频进行读取,并检测出人脸,然后进行PCA 降维,最后用SVM进行人脸识别,识别率94%左右。(Based on python + opencv face recognition, a video was read, and face detection, and then PCA dimension reduction, and finally SVM face recognition, recognition rate of about 9
FPGA_hslogic_face
- FPGA代做,通过matlab实现PCA人脸识别算法,并计算识别率(n the FPGA generation, the PCA face recognition algorithm is realized by MATLAB and the recognition rate is calculated.)
FaceRecognition
- 基于matlab平台的人脸识别 简单代码 识别率还行 大家可以看看(Based on the matlab platform face recognition simple code, the recognition rate is also ok you can see.)
BP神经网络
- 第一个m文件:构造、训练BP神经网络并计算其识别率;第二个文件将进行人脸检测。注意:orl人脸数据库需要在网上下载。(The function of the first m file is to construct and train the BP neural network and calculate its recognition rate. The second is the detection of face. Note: the ORL face database needs to
facerecognition
- JAVA开发的人脸识别,能通过摄像头识别人脸,识别率不错(JAVA developed face recognition, through the camera to identify the face, the recognition rate is good.)
表情识别数据集
- 整个数据库一共有213张图像,10个人,全部都是女性,每个人做出7种表情,这7种表情分别是: sad, happy, angry, disgust,surprise, fear, neutral. 每个人为一组,每一组都含有7种表情,每种表情大概有3,4张样图。这样每组大概20张样图,目前在这个数据库上的识别率已经很高了,不管是person independent 或者是person dependent。识别率都很高。这个数据库可以用来熟悉人脸表情识别的一些基础知识,包括特征提取,分类等。