Piotrs-Image-a-Video-Matlab-Toolbox

用于求取三维点云数据的法向量，我的人脸建模就是用的这个，效果很好，但必须保证点云没有重叠的，否则会出现严重错误。(Strike a 3D point cloud data for normal vectors, and my face is to use this model, the effect is very good, but must ensure that there is no overlap of the point cloud, there would be a serious mistake.)

qquick 学习学习编写qt的快速应用程序的一种qml语言的学习(qquick learning learning qt programming quick application of a qml language learning)

用于计算在三维点云处理过程中的局部点云面积估算，精度很高。(Used to calculate the three-dimensional point cloud processing local point cloud area estimation accuracy is very high.)

关于快速排列的动画演示，由java swing写成(quick sort)

vb 饼状图和柱状图，这里是一个demo，并含有注释，方便新手学习(vb,circle chart and point chart)

通过MATLAB程序可以很容易的画出三维的图像，让初学者一目了然。(MATLAB program can easily draw a three-dimensional image, so that beginners at a glance.)

2012年最新二维码开发(C#)源程序代码，VS2008开发，是C#工具开发二维条码应用最理想的参考范例。提供动态链库接口开发方法，条码图像打印、条码参数设置和非托管API调用方法，并教您如何将文本、图像、声音和指纹压缩放入二维码中。二维条码种类包括：PDF417,Qr_Code,DataMatrix和HanXin等(The 2012 two-dimensional bar code development (C#) source code, VS2008 development, the development of the best examples of reference of the application of the two-dimensional code C# tools. Unmanaged API calls method provides a dynamic link library interface development methodology, and teach you how to compress the image, voice and fingerprint into the two-dimensional code. Types of two-dimensional code including: of PDF417, Qr_Code, DataMatrix and HanXin)

一个比例和方向自适应均值漂移跟踪算法（SOAMST） 提出本文所要解决的问题，如何估计的规模和方向 改变均值漂移下的目标跟踪框架。在原来的均值偏移 跟踪算法，可以很好地估计目标的位置，规模的同时， 方向的变化，不能自适应估计。考虑到图像（重量） 是来自于目标运动模型和候选模型可以代表的可能性，一个 像素属于目标，我们证明了原来的均值漂移跟踪算法可以 推导出的重量图像的零阶和一阶矩。随着零阶 矩和目标模型和候选模型之间的Bhattacharyya系数， 提出了简单而有效的方法来估计的规模为目标。然后一种方法， 利用估计的区域和第二阶中心矩，提出 自适应地估计目标的宽度，高度和方向的变化。广泛 实验来证实所提出的方法，并验证其可靠性 规模和方向变化的目标。(A scale and orientation adaptive mean shift tracking (SOAMST) algorithm is proposed in this paper to address the problem of how to estimate the scale and orientation changes of the target under the mean shift tracking framework. In the original mean shift tracking algorithm, the position of the target can be well estimated, while the scale and orientation changes can not be adaptively estimated. Considering that the weight image derived from the target model and the candidate model can represent the possibility that a pixel belongs to the target, we show that the original mean shift tracking algorithm can be derived using the zeroth and the first order moments of the weight image. With the zeroth order moment and the Bhattacharyya coefficient between the target model and candidate model, a simple and effective method is proposed to estimate the scale of target. Then an approach, which utilizes the estimated area and the second order center moment, is proposed to adaptively e)

通过图像模板匹配，完成数字图像的平面应力与应变分析(Complete plane stress and strain analysis of digital image)

利用MATLAB软件编程实现三维重建，对CT图像实现三维体绘制。(CT images of three-dimensional volume rendering reconstruction)