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UFR2.0
- 通过人脸图像归一化，人脸检测，特征提取等处理后，实现人脸识别功能-Through the Human face image normalization, face detection, feature extraction, such as treatment, the realization of face recognition feature
face
- 完整的表情识别系统一般包括人脸表情图像捕获、预处理、人脸检测与定位、 人脸分割与归一化、人脸表情特征提取、人脸表情识别。本文着重研究了人脸表 情特征提取、特征选择及表情分类等关键问题，并提出了一些改进的方法，同时 进行了仿真实验-Complete expression recognition systems typically include facial expression image capture, preprocessing, face detection and loca
Face_recognition
- 人脸识别程序。算法部分目前分为4个模块：人脸对齐、光照归一化、特征提取和选择、子空间降维，每个模块是一个项目，每个项目生成一个dll供功能部分隐式调用-Recognition program. Part of the algorithm is currently divided into four modules: face alignment, illumination normalization, feature extraction and selection, subspace dime
orl_cut_image
- 这是人脸表情识别中的预处理。主要有尺度归一化和灰度归一化，是表情识别中重要的部分-This is a human facial expression recognition preprocessing. There are gray-scale normalization and normalization, is an important part of the expression recognition
jaiteng
- 迭代自组织数据分析，数据模型归一化，模态振动，人脸识别中的光照处理方法。- Iterative self-organizing data analysis, Normalized data model, modal vibration, Face Recognition light treatment method.
FaceTools-master
- 可以对图像进行归一化，实现人脸检测和对其(The image can be normalized to realize face detection and to it)