TriangleMesh

实现对函数的步长加速法寻优，并作图直观显示寻优过程和效果(The step function to achieve acceleration method optimization and mapping visual display optimization process and effects)

旋转的文字球：滑动鼠标，控制文字球的旋转方向(a rotation ball made of characters: row mouse,you can control the orientation of the ball)

使用c++ 及 OpenGL 显示.obj 加载纹理(show the file .obj and render the texture)

说明：  用matlab实现的EZW编码解码，对图像进行小波变换，EZW算法搜索小波系数矩阵，包括熵编码（HUFFMAN）(achieved using Matlab EZW codec, the image wavelet transform, EZW wavelet algorithm search coefficient matrix, including entropy coding (HUFFMAN))

运用Visual C++编译器实现的3D图像变成代码，主要实现图像绘制(Using Visual C++ compiler implements the 3D image into a code, the main image rendering)

三维切片：读取STL文件并进行按层切片的简单示例程序(Three-dimensional slices: Read STL file and layer slices by a simple example program)

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.)

国外的一个2D 相位解卷绕的代码。用matlab及c++编写。适用于三维重建领域研究人员使用。(A foreign 2D phase unwrapping code. Using matlab and c++ prepared. Researchers use applicable to the field of three-dimensional reconstruction.)

二维磁流体计算程序，可根据问题干煸，已有改变成三维的版本(Two-dimensional MHD calculation program, according to the problem dry stir, has changed into a three-dimensional version of the)

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)