pipei

该源码为目标检测和跟踪算法 包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (The source code for target detection and tracking algorithm include: 1 Static background background prediction target detection 2 Static background frame difference method for target detection 3. Mean Shift tracking method 4 multi-target tracking methods focus)

一个很好类子来说明类模板的使用，可以比较明了类模板的使用方法，最好进行单步调试(use of class template )

说明：  经典图论，其中叙述了图论的经典算法等，如最大流、最小割等相关算法。(Classical graph theory, graph theory, which describes the classical algorithms, such as maximum flow, minimum cut, and other related algorithms.)

采用MFC，实现遥感图像的基本增强，滤波，变换等功能。还可以保存数据。(Using MFC, to achieve the basic enhancement of remote sensing images, filtering, transformation and other functions. You can also save data)

这是一个应用VC++编写的基于摄像头读取人脸的人脸识别和人脸检测软件，其中引用了MATLAB的系统函数，是一个非常不错的人脸识别软件，这个系统在我校论文答辩审核中获得了优秀的成绩。希望对大家有用(This is an application-based VC prepared to read camera Face to Face Recognition and face detection software. cited in the MATLAB system function, is a very good face recognition software. The system in my school examination papers reply obtained outstanding achievements. We hope to useful)

Image enhancement is a processing on an image in order to make it more appropriate for certain applications. It is used to improve the visual effects and the clarity of image or to make the original image more conducive for computer to process. Contrast enhancement changing the pixels intensity of the input image to utilize maximum possible bins. We need to study and review the different image contrast enhancement techniques because contrast

实现原始的JPEG图片编解码，不借助任何的第三方库，纯C++。(To achieve the original JPEG image decoding, without using any third-party libraries, pure C++.)

视频演示算法包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (Algorithm for video presentation include: 1. Static background background prediction target detection 2. Static background frame difference method for target detection 3. Mean Shift tracking method 4. Gravity multi-target tracking method)

c++实现的sift，可以分步观看实现效果(c++ implementation of the sift, you can watch step by step to achieve results)

根据RBM深度网络（Hinton，2006）进行MINST手写文字的分类器的训练，利用训练得到的权值制作了这个小程序，通过这个程序可以看出训练结果对数据集内的测试样本和训练样本都能进行很好的识别，但是对其他的手写字体识别就没有那么好了。(According to RBM depth network (Hinton, 2006) conducted MINST handwritten text classifier training, using the training to get the right value to produce this small program, this program can be seen through the results of the training data set and the training sample test samples are can be well identified, but on the other handwriting recognition is not so good.)