Server

高斯混合模型的源代码。从文件中读取数据，用三个高斯混合模型进行处理(Gaussian mixture model of the source code. Read from the file data, using three Gaussian mixture model for processing)

光流法、帧间差分法、高斯背景模型差分法，在opencv环境下实现运动目标检测(moving objective detection matlab)

高斯有色噪声，有色噪声的谱估计及其在雷达中的应用(gauss noise)

对图像变形的一些基本算法的介绍和功能的描述等 (about marphing )

基于双目视觉的三维重建，包含了重建过程中的基本步骤。(Binocular vision-based three-dimensional reconstruction, including the reconstruction of the basic steps of the process.)

卡尔曼滤波算法，opencv代码，鼠标跟踪(Kalman filter algorithm, opencv code, mouse tracking)

数字图像处理方面的常用操作 人脸识别 图像打开和保存 类似photoshop操作 (Digital image processing operations commonly used face recognition and preservation of the image to open a similar operation photoshop)

在分析聚束合成孔径雷j盘(SAR)方位向时频关系的基础上，提出了一种新的全孔径分辨率SAR成像算法。 根据SAR在条带与聚束模式下回波信号之间的差别，利用现有成熟的条带SAR成像算法实现先对聚束SAR各方位向子 孔径成像，而后再将各方位子孔径带宽合成为全孔径带宽，以形成具有全孔径分辨率的SAR图像，极大降低了系统PRF 的要求。(In the analysis of spotlight synthetic aperture radar dish j (SAR) azimuth based on the time-frequency relationship, a new full-aperture resolution SAR imaging algorithm. According to SAR in strip and spotlight mode, the difference between the echo signal, the use of existing mature band SAR imaging algorithm first bit of the spotlight SAR the parties to the sub-aperture imaging, and then place then all the bandwidth synthetic aperture the bandwidth for the full aperture to form a full aperture resolution SAR images, greatly reducing the system PRF requirements.)

LK 和HS光流代码，初学者可用，带有误差分析(LK optical flow and the HS code is available for beginners, error analysis with)

程序将界面与数据处理分开，界面采用MFC的对话框模板，对注册、训练、识别和主界面分别建立一个类，通过消息处理函数与用户进行交互，利用多线程来实时显示图像。 数据处理又分为了CFaceAlign（人脸检测+几何归一化）、CLightPrep（光照归一化）、CFaceFeature（Gabor特征提取）、CSubspace（计算Fisherface子空间）四个类，还有一个类 CFaceMngr 负责管理界面与数据之间的交流。这样的程序结构使对界面和算法彼此独立，互不影响。 每个类的具体方法请见相应头文件中的注释。(The program will interface with the data processing separate interface using MFC dialog template, registration, training, recognition and the main interface, respectively, to create a class that interacts with the user through a message handler, using multiple threads to display images in real time.   Data processing is divided into a CFaceAlign (Face Detection+ geometric normalization), CLightPrep (illumination normalization), CFaceFeature (Gabor feature extraction), CSubspace (computing Fisherface subspace) four categories, as well as a class is responsible for managing CFaceMngr interface and data exchange between. Such a program structure allows for interfaces and algorithms are independent of each other. Specific methods of each class, see the comments in the appropriate header files.)