搜索资源列表
Face-Recognition--System
- 实现人脸图像的采集 预处理 特征提取和图像变换-Collection of face images to achieve feature extraction and image transform preprocessing
face-recognition
- pca又称主成分分析,主要用来提取图像的主要成分,作为特征提取一个重要算法,将其用于人脸识别-pca, also known as principal component analysis, mainly used to extract the main component of the image, as a key feature extraction algorithm, be used in face recognition
Nicolas_PCA
- 本程序含人脸特征提取的主成分分析(PCA)的源程序,希望对大家有用-The face feature extraction process with principal component analysis (PCA) of the source, we hope to be useful
Yale_5G
- Yale,PCA,SVM,matlab,人脸检测,特征提取,人脸识别.-Yale, PCA, SVM, matlab, face detection, feature extraction, face recognition.
chengxu
- 用于人脸特征提取的2D2DLDA、2D2DLPP、2D2DPCA算法,由原本的一维特征提取改善为二维特征提取,大大提高了其识别率。-For facial feature extraction 2D2DLDA, 2D2DLPP, 2D2DPCA algorithm, from the original one-dimensional two-dimensional feature extraction feature extraction to improve, greatly improve t
rlycl
- 人脸特征提取预处理 包括灰度拉伸,中值滤波,同态滤波,直方图均匀化-Facial feature extraction preprocessing, including gray-scale stretch, median filtering, homomorphic filtering, histogram equalization
gaborsvm1
- 先用gabor 小波滤波器,做特征提取,然后用支持向量机(SVM)做分类,来实现人脸检测.需要用matlab 2010 或更新的版本才能运行-the code is used for face detection.Firstly it use gabor wavelet filter for feature extraction,Secondly it use support vector machine (SVM)for classification.matlab 2010 required.
LBP
- LBP算法,应用于识别,特征提取等多方面的一种潜力算法,主要实现图像的纹理分类-LBP algorithm, used in recognition, feature extraction algorithms and other aspects of a potential,Mainly for image texture classification
VCPP-face-recognition
- 这是一个用vc++编写的人脸识别系统,输入一张普通的人脸图像,通过对人脸进行预处理,特征提取,以及模板匹配等操作,最后作出识别结果-This is a written by vc++ face recognition system, input a regular face image preprocessing, through to the face, feature extraction, and template matching operation, and finally make
Jonathan-Huangpca-pca-jiang-wei
- 人脸特征提取LDA特征,Jonathan Huang大师编的降维。-Facial feature extraction LDA dimensionality reduction of features, master series.
face---PcaFC
- 利用主成分分析的特征子空间进行人脸特征提取,通过人脸重建进行人脸识别-Feature subspace using principal component analysis for facial feature extraction for face recognition, face reconstruction
Facial-Feature-Tarcking
- 研究优化人脸特征提取问题,针对长期以来在不贴标记点的情况下用传统的光流、Snake、可变模板等方法对纹理特征变化大的特征点不能有效跟踪,并且解决单独采用Gabor 小波系统开销大等问题,为了在人脸图像中提取准确信息,提出了人脸特征点的跟踪方法,分组采用改进的光流法和弹性图匹配的方法进行特征点跟踪。对眼睛、眉毛、上下眼皮等14 个表 情变化不大的特征点使用光流法进行跟踪,最后对变化大的嘴部8 个特征点运用Gabor 小波的弹性图匹配方法进行仿真。-Gabor wavelet research
LDA
- 人脸特征提取的线性差别分析法LDA,可以提高样本在子空间中的可分性-algorithm of LDA of face detection by matlab
nmf
- 基于非负矩阵分解(NMF)的人脸特征提取算法,其基本思想是找到一个母性子空间,是的构成子空间的基图像的像素点都是正值-algorithm of NMF of face detection by matlab
2dwave
- 使用二维小波进行分解,再进行重构的程序。重要用于人脸特征提取。-Using two-dimensional wavelet decomposition remodeling program. Important for face feature extraction.
renliantezhengquyu
- 首先利用人脸的色彩特征和自适应阈值法实现特征候选区域和人脸肤色区域的分离,然后利用人脸的几何特性将连通的特征候选 区域保留下来作为人脸特征区域。后续的特征提取可以在这些人脸特征区域中完成。一般的人脸特征提取方法都可以将该方法作为提高效 率的预处理操作。实验证明,该方法具有高效率、低计算量的特点,并且受人脸表情、图像角度和背景的影响较小。-First, the use of the color characteristics of the human face and adaptive t
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- 利用主元分析和奇异值分解进行人脸特征提取的方法(并详细阐述其在PQRSQT中的实现过程(包括读取图像文件U计算均值脸U求特征值和特征向量(计算人脸特征参数-实现过程均给出了MATLAB代码-Using principal component analysis and singular value decomposition facial feature extraction method (and detail its in the PQRSQT in the implementation pr
feature-points-extraction-from-faces
- 人脸特征提取 feature points extraction from faces-feature points extraction from faces
matlab--skin
- matlab基于肤色的人脸特征提取,rgb转换到ycrcb空间-based on skin color segmentation matlab face feature extraction, rgb color space conversion to Ycrcb
Gabor-feature
- Gabor特征提取 包括8个方向以及5种不同尺度 可用于人脸特征提取-Gabor feature extraction, including eight directions and 5 different scales can be used for facial feature extraction