Triangle-of-Point-Cloud

flac3d自定义本构模型实例演示，可以帮助数值模拟爱好者学习如何自定义本构模型。(flac3d custom constitutive model examples demonstrate, numerical simulation can help enthusiasts to learn how to customize the constitutive model.)

matlab采用二进小波实现边缘检测的源代码(matlab using Dyadic Wavelet Edge Detection)

Matlab 三维点云三角化 不是平面域的三角化 是三维点云三角化 亲身测试绝对可用！(Triangle of Point Cloud)

说明：  基于贝叶斯(BAYES)阈值的小波(WAVELET)图像去噪算法源代码(Based on Bayesian (BAYES) threshold wavelet (WAVELET) image denoising algorithm source code)

连续信号的采样与重构,主要说明信号采样与重构程序(Continuous signal sampling and reconstruction, mainly explain the procedure of signal sampling and reconstruction)

一个VRML的示例，通过鼠标点击可以使场景内的灯管发光(An example of a VRML through mouse clicks can make a scene inside the lamp light)

利用Kalman Filter进行机动目标跟踪的例子,附有详细的说明文档,(Examples of using Kalman Filter for maneuvering target tracking, a detailed documentation,)

说明：  基于vtk的三维重构与裁切: 1.16位非压缩位图的读取与设置. 2.图像数据载入映射器 3.裁切平面的设置 4.边界的设置与显示 5.三维重构 注:需安装vtk4.0以上版本(It s about 3D reconstruct and clip based on VTK including reading and configration of 16 bits non_contracted bitmaps,the mapper for image data loading, configration of plane for clip,configration and display of borders and 3D reconstruct.(PS:VTK 4.0 or above version is needed))

转动的彩色立方体（1~2人）谭飞、吴颖颖 1) 绘制一个不停转动的彩色立体球，可以绕着任意方向旋转； 2) 采用一定的光照明技术，考虑环境光、反射光以及镜面光的作用； 3) 采用消隐算法，体现立方体表面的遮挡关系； 4) 具有较好的动画效果，消除闪烁现象； 5) 不可以采用OpenGL中的函数。 (Rotating color cube (1 ~ 2)谭飞,吴颖颖1) draw a non-stop rotation of the color three-dimensional ball, you can spin around in any direction 2) the use of certain lighting technology, consider the ambient light, reflected light and the mirror The role of surface light 3) the use of blanking algorithm, reflecting the relationship between cube block surface 4) has good animation effects, to eliminate flicker phenomenon 5) can not be used in a function of OpenGL.)

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)