MODPCNNFUSION

采用了Harrtraining和离子滤波算法实现了拥挤人群人头计数，非常有用。VC++和Opencv开发，采用Oepncv中的Harrtraining训练一个分类器即可运行(Human detection and tracking in high density crowds is an unsolved problem. Standard preprocessing techniques such as background modeling fail when most of the scene is in motion. We integrate human detection and tracking into a single framework, and in- troduce a conrmation-by-classication method to estimate condence in a tracked trajectory, track humans through occlusions, and eliminate false positive detections.)

可根据需要自定义窗口形状，用于各种特效窗口开发(Customizable window shape, for a variety of special effects needed to develop window)

图形处理的部分，能进行图像的中值过滤处理(To the median filter for image processing)

压缩感知基追踪算法，实现二维图像的小波变换以及图像重构(Compressed sensing based tracking algorithm, wavelet transform two-dimensional image, and image reconstruction)

Ocr related documentataion

主成分分析PCA源代码（C++，matlab）主成分分析PCA源代码（C++，matlab）(Principal Component Analysis PCA source code (C++, Matlab), principal component analysis PCA source code (C++, Matlab))

图像配准程序，包括角点提取，配对，提纯等操作(image registeration ,including connor detection,match and so on)

《OpenCV基础教程》于仕琪主编，书中所有源代码下载，基于OpenCV的图像处理技术(" OpenCV-based tutorial," in Shi Qi editor of the book to download all the source code, based on OpenCV image processing technology)

基于纹理度量的图像分割，适用于遥感图像，利用到K-mean算法(texture measurement based on the image segmentation, applicable to remote sensing images, the use of K-mean algorithm)

泊松融合在某种意义上解决了图像融合的问题，但其在融合的过程中仅仅考虑了融入图像的梯度，而没有利用背景图像的梯度，因此，在使用泊松融合的过程中，需要对融入区域的标记较为准确，否则，会造成背景纹理的丢失，视觉上可以明显觉察图像融入的痕迹。因此，对公式稍作修改，在考虑前景的同时考虑背景的变化，可以得到更优的结果。(Poisson convergence in a sense solved the problem of image fusion, but it only considers the integration of image gradient in the integration process, but not the use of a background image gradient, therefore, the use of the Poisson integration process, the need for more accurate marker into the area, otherwise, it will result in the loss of background texture, image integration can clearly perceive the visual traces. Therefore, the formula slightly modified, in considering the prospect of taking into account the changes in the background, you can get better results.)