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openCV-2.2_collection
- 自己整理的opencv源码分析，是关于opencv2.2的，里面也有自己的翻译，如果大家喜欢，我陆续会把源码分析一个个上传完毕-Opencv source of his finishing is about opencv2.2' s, which also has its own translation, if you like, I will gradually upload one complete source code analysis
OPencv1
- 这是一个自己收集的关于opencv应用的一些小例子。。大家一起学习-This is a collection of his application on some small examples of opencv. . We will study together
YU-Shiqi-code-of-opencv
- 这是于仕其编的关于opencv的基础教程里面所有例子的代码-This is the official compilation of his tutorial on the basis of opencv code for all examples
Qt_RobHess_Sift
- sift算法在cv领域的重要性不言而喻，该作者的文章引用率在cv界是number1.本篇博客只是本人把sift算法知识点整理了下，以免忘记。本文比较早的一篇博文opencv源码解析之(3)：特征点检查前言1 中有使用opencv自带的sift做了个简单的实验，而这次主要是利用Rob Hess的sift源码来做实验，其实现在的opencv版本中带的sift算法也是Rob Hess的，只是稍微包装了下。 下面来做下试验,试验sift代码采用Rob Hess的代码，opencv目前版本中的sift
location
- 自己实现的五官精确定位算法，可以用矩形框出五官的位置。-Realize his facial features precise positioning algorithm to the location of the facial features, you can use the rectangle.
flandmark-master
- 能夠準確的detect到人的五官的位置 好比說眼角，嘴唇的嘴角，同時也是即時處裡的-Able to accurately detect the location of the person' s facial features like saying his eyes, the lips, the mouth, but also the instant at
tensor-voting
- 张量投票他的项目包含有表决权框架作为实施 组类，工程toghether作为一个“机制”-his project contains the implementation of the voting framework as a set of classes that works toghether as a "mechanism" (see "Doing hard Time") to give principally 4 use cases
1
- Harris角点检测原理及实现，程序不是我写的，csdn的crzy_sparrow写的，感兴趣可以看他的博客！-Harris corner detection principle and implementation, the program is not what I wrote, csdn of crzy_sparrow write, interested can look at his blog!
CamCalib_OPENCV
- 计算机视觉中相机内外参数标定，利用opencv函数，实现内外参数计算，标定误差等等，可以直接运行。内含自己拍的标定版图像 vs2008-Calibration of the camera parameters in computer vision, using the opencv function, to realize the internal and external parameters calculation, the calibration error and so on, can
LPRS-Python-opencv-
- 这个是自己用Python2.7写的基于opencv的车牌识别,目前识别率还是不怎么高,车牌定位采用的是形态学变换,分割是自己写的一个算法,识别部分采用的是kNN算法,有详细的注释!-This is his written in Python2.7 opencv based license plate recognition, the recognition rate is not very high, license plate location is the morphological tra