搜索资源列表
abc
- 利用opencv裡的hmm function 來達到人臉識別的功能
HMMsource
- HMM用于人脸识别，从OPENCV里提取出来的,非常经典的说-HMM for face recognition, OPENCV extract from the very classical said
HMMDemo
- 基于opencv的HMM人脸识别，可连接摄像头实时拍摄识别！（opencv1.0）-Opencv of HMM-based face recognition, can be connected to real-time camera shot Recognition! (Opencv1.0))
HMMDemo
- 基于Opencv编辑的人脸识别工具，可以直接从USB摄像头获取人脸，依据HMM模型实现-Based on the Opencv editing tools that can directly face recognition from the USB camera for face, HMM. According to the model
facerecognition
- 采用OpenCV进行人脸识别，隐马尔科夫链的应用，由混合分量来分割HMM的每个内在状态的所有观测值，运用现有的图像观测值分割为所有嵌入和内部的HMM函数，计算可能的变换矩阵-Using OpenCV for face recognition, hidden Markov chain applications, from the mixed components to split the internal state of each HMM all observations, use of the
HMM_face_recognition
- 用隐形马可夫模型来做的人脸识别程序,利用了很多opencv的东西-face recognition by using Hidden markov model, opencv is included
2DLDAwiththeSVM-basedfacerecognitionalgorithm
- 二维线性鉴别分析(2DLDA)算法能有效解决线性鉴别分析(LDA)算法的“小样本”效应，支持向量机 (SVM)具有结构风险最小化的特点，将两者结合起来用于人脸识别。首先，利用小波变换获取人脸图像的低频分量，忽 略高频分量：然后，用2DLDA算法提取人脸图像低频分量的线性鉴别特征，用“一对多”的SVM 多类分类算法完成人脸 识别。基于ORL人脸数据库和Yale人脸数据库的实验结果验证了2DLDA+SVM算法应用于人脸识别的有效性。-”Small sample size”problem
hmm12345
- 基于隐形马尔科夫的特征提取技术，hmm，opencv-Extraction technique based on the characteristics of stealth Markov，hmm，opencv
HMMDemo
- 基于HMM算法实现人脸识别，利用opencv开源视觉库来实现人脸识别-Face recognition algorithm based on HMM
Oencv(HMM)
- OpenCV基于隐马尔可夫模型（HMM）的人脸识别-Research on Face Recognition Model Based On Simplifled Pseudo 2D Hidden Markov Model
OpenCV基于隐马尔可夫模型（HMM）的人脸识别
- OpenCV基于隐马尔可夫模型（HMM）的人脸识别源程序(OpenCV based on Hidden Markov model (HMM) for face recognition source program)