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自己按照网上的源码做的3D图形变化的修改，实现一个BMP图片的旋转，基本实现，但还没有完全完成(Your online source according to the 3D graphics make changes changes to implement a BMP image of the rotation, basically, but not entirely complete)

直接运行TestMyCrust.m, 读取点云txt,或者直接加载mat文件 运行需要几分钟，耐心等待 完成后运行trianglenormal.m, 生成三角面片的法向量 运行完成得到tri.txt（组成三角面片的点的编号信息）,trinormal.txt(每个三角面片法向量数值)，diandian.txt(每个点云信息) 然后将三个数据当做stl_gen.exe的输入文件，得到trisuface.stl文件(run TestMyCrust.m, read point cloud file txt, or load mat file)

机械画图，曲柄摇杆机构，用matlab实现的，希望大家喜欢(Mechanical drawing, crank rocker mechanism, using matlab to achieve, I hope you like)

利用IDataGraph等接口对三维图形进行坡度分析，通视分析等(IDataGraph use three-dimensional graphics and other interfaces slope analysis, through visual analysis)

说明：  在VC下利用directX9.0写的很好的3D图形编程的例子，包括.x文件的读取，纹理的加载！适合初学者练手！(in VC directX9.0 write using a good 3D graphics programming examples, including. X document read, texture loading! For beginners to practice hands!)

视频实时3d重建，以视频的形式实时的将二维画面转换为3d画面。(he paper presents a system for automatic, geo-registered, real-time 3D reconstruction from video of urban scenes. The system collects video streams)

基于ABAQUS UMAT二次开发的三维邓肯-张本构模型(A program for 3-D Ducan-Zhang model based on ABAQUS UMAT)

说明：  实时图形设计 3d场景漫游 3dmax模型 场景中包括树木 房屋 道路 移动小车 以及 billboard 绘制的树木 支持人机互动 场景漫游(This code is the assignment for our real-time graphic designing. It includes many scenes like houses,trees using the billboard skill, roads and the cars.)

说明：  对偶四元数应用于空间坐标变换，和对偶四元数和齐次矩阵的转换(Dual quaternion coordinate transformation applied to space, and dual quaternion and homogeneous matrix conversion)

最大类间方差法是由日本学者大津(Nobuyuki Otsu)于1979年提出的,是一种自适应的阈值确定的方法,又叫大津法,简称OTSU。它是按图像的灰度特性,将图像分成背景和目标2部分。背景和目标之间的类间方差越大,说明构成图像的2部分的差别越大,当部分目标错分为背景或部分背景错分为目标都会导致2部分差别变小。(The largest between-class variance method was proposed by the Japanese scholar Nobuyuki Otsu in 1979. It is an adaptive threshold determination method, also known as the Otsu method, or OTSU for short. It is based on the grayscale characteristics of the image and divides the image into two parts: the background and the target. The larger the variance between the background and the target, the greater the difference between the two parts that make up the image. When the part of the target is wrongly divided into backgrounds or part of the background is mis-divided into goals, the difference between the two parts will be smaller.)