资源列表
test
- opencv和mfc结合 ，单文档应用程序，可用来打开电脑中的图片 并显示在窗口中-opencv and mfc combination of single-document application, can be used to open the computer and displayed in the window picture
mic_expression-recognition
- 运用LBPTOP对动态序列图像进行特征提取，libsvm用做分类器，进行微表情识别。程序绝对完整，能够运行出结果-LBPTOP is used to extract features the dynamic image sequences, and libsvm is used as a classifier to recognize the micro expression. Program is absolutely complete, can run out the results
ViBe
- windows下vibe测试程序，可以测试vibe的效果-Vibe under the windows test procedures, you can test the effect of vibe
Computer-Vision
- Computer Vision A Modern Approach 2nd Edition
Advances.in.Image.And.Video.Segmentation
- advances in image and video processing
3Dmodel
- surf算法提取同名点，然后根据相机定标参数，计算同名点三维坐标。-extract the same points using surf algorithm, based on the camera calibration parameters, calculate the three-dimensional coordinates of the corresponding points.
Showpic
- 实现功能：打开图像，直方图均衡化，RGB反转，图像缩放，各种滤波，各种分类，几何校正等。 -Function: open the image, histogram equalization, RGB inversion, image scaling, various filtering, various classification, geometric correction, etc..
ActiveModels
- ActiveModels contains a Matlab toolset and examples for training and fitting AAMs (Active Appearance Models). Please refer to the code and included examples for its function. You must have an annotated database to use its features.
DynamicWorld
- 使用opengl中的纹理贴图，光照，以及3D模型导入，构造了一个房间，能够使用鼠标和键盘实现虚拟漫游（w,a,s,d）-Use opengl the texture mapping, illumination, and 3D model import, construct a room, be able to use the mouse and keyboard to achieve a virtual roaming (w, a, s, d)
tocr20
- 图片中字符识别，还不错，网上下的，边缘检测，字母，数字，符号识别-The picture character recognition, but also good under line, edge detection, letters, numbers, symbols identify the
SkeletonBasics-D2D
- 使用KINECT获取骨骼图像的源码，在vs平台下使用C++编写。-Use KINECT get bone image source, written using C++ in vs internet.
vlfeat-0.9.20-bin.tar
- 常用工具包，特征提取方法，如HOG，sift等特征，分类方法如决策树，svm等(Commonly used toolkits, feature extraction methods, such as HOG, sift and other features, classification methods, such as decision trees, SVM, etc.)