变化检测

基于图像的纹理特征参数的MVA的提取，该方法使用方便，理解简单。(Image-based texture feature extraction parameters of MVA, the method easy to use, easy to understand.)

通过帧差追踪小车

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源码也是采用Rob Hess的。代码可以在他的主页上下载：http://blogs.oregonstate.edu/hess/code/sift/ 这里我下载的是windows版本的，并采用Qt做了个简单的界面。(sift algorithm is self-evident the importance of the cv field, the author of the article referenced in the cv sector is number1 this blog I just sift algorithm knowledge compiled under, so as not to forget. This article compares the earlier blog post opencv source code analysis (3): check the preface of the feature points 1 the opencv bring their own sift to do a simple experiment, but this time Rob Hess' s sift source to experiment. In fact, with the opencv version sift algorithm is Rob Hess, only slightly packing the next. Below to do the next test, test sift code using the code of Rob Hess, sift source opencv version of Rob Hess. The code can be downloaded on his home page: http://blogs.oregonstate.edu/hess/code/sift/ here I downloaded the windows version, and using Qt to do a simple interface.)

VC中绘制坐标系、网格、常用数学函数以及辅助功能（背景色切换、坐标标题修改等）(vc draw)

基于多尺度超像素的显著性检测代码和文章(Saliency Detection with Multi-Scale Superpixels)

对灰度图像进行插值，经运行，大家可放心下载。谢谢(Gray image interpolation, after running, we can rest assured that download. Thank you)

说明：  随机森林的行人检测。针对视频和图像中快速、准确的行人检测问题,提出了一种分层次的、全局信息和局部信息相结合的行人检测算法。该方法以随机森林分类器为基础。(Pedestrian detection based on random forest)

Image Database 2.5.0 (w/ thumbnails)

几种插值方法，双线性，三次，最邻近，sinc(Several interpolation, bilinear, cubic, nearest neighbor, sinc)

通过C#生成二维码