from matplotlib.tri import Triangulation, TriAnalyzer, UniformTriRefiner import matplotlib.pyplot as ----------------------------------------------------- # Generating the initial data test points and triangulation tri = Triangulation(x_test, y_test) ntri = tri.triangles.shape[0] # Some invalid data are masked out ---------------------------------- # User options for plots plot_tri = True # plot of base triangulation plot_tri: ax.triplot(tri, color='0.7') # 4) plot of the unvalidated triangles from naive Delaunay Triangulation
[CGAL]带岛多边形三角化 CGAL带岛多边形三角化,并输出(*.ply)格式的模型 模型输出的关键是节点和索引 #include <CGAL/Triangulation_vertex_base_with_id _2.h> #include <CGAL/Triangulation_face_base_with_info_2.h> 因此注意这两个泛型,对比不带信息的 #include <CGAL/Triangulation_vertex_base _2.h> #include <CGAL/Triangulation_face_base_2.h>,这两个增加了部分信息作为拓展。 _2.h> #include <CGAL/Triangulation_vertex_base_with_id_2.h> #include <CGAL/Triangulation_face_base_with_info ::Constrained_triangulation_face_base_2<K, Fbb> Fb; typedef CGAL::Triangulation_data_structure
整体框架如图所示 1)Triangulation Triangulation类相当于前处理的几何建模和网格划分。Triangulation存储了网格的几何和拓扑性质,如单元接触形式和顶点位置。 一个triangulation对象不知道我们要在这个网格上使用的有限元的任何信息,它甚至都不知道它的单元的形状,它只知道2维时有4个面和4个顶点,三维时有6个面、12条边和8个顶点,其他信息都在映射类中定义 类按照finite elements对自由度的要求在triangulation的节点、边和单元内部分配自由度,并获得每个自由度的全局标识。 如同triangulation对象,DoFHandler类的大部分操作也是通过对单元进行循环来完成的,我们可以得到的信息包括:单元的几何和拓扑信息(该信息在之前通过triangulation的迭代器获得 ),当前单元的自由度的全局标识,从一个存储triangulation全部自由度相关联的值的数据向量中提取当前单元的自由度相关联的值。
Envelope_2 34.Envelope_3 35.Filtered_kernel 36.Generator 37.HalfedgeDS 38.Heat_method_3 39.Hyperbolic_triangulation _2 66.Periodic_3_mesh_3 67.Periodic_3_triangulation_3 68.Periodic_4_hyperbolic_triangulation_2 69.Point_set 117.Triangulation_2 118.Triangulation_3 119.Visibility_2 120.Voronoi_diagram_2 五.CGAL Demo 1.AABB_tree _2 23.Periodic_3_triangulation_3 24.Periodic_4_hyperbolic_triangulation_2 25.Periodic_LIoyd_3 26.Polygon _2 40.Triangulation_3 41.Triangulation_3_Geomview_demos
_2 D:\local\CGAL-4.13.2\examples\Triangulation_2> mkdir build D:\local\CGAL-4.13.2\examples\Triangulation _2> cd build D:\local\CGAL-4.13.2\examples\Triangulation_2\build> cmake-gui … 打开CMake界面后(一个非常变态的东西出现了 ) 在where is the source code中输入:D:\local\CGAL-4.13.2\examples\Triangulation_2 下一栏输入:D:\local\CGAL-4.13.2 \examples\Triangulation_2\build 然后Configure 下选择vs版本和系统版本 done结束 再选择Generate 然后打开在Triangulation_2下生成的. sln文件(位置:D:\local\CGAL-4.13.2\examples\Triangulation_2\build) 将draw_triangulation_2设置为启动项 点击运行 在VS中使用
np.min(z)) #----------------------------------------------------------------------------- # Creating a Triangulation np.cos(angles)).flatten() y = (radii * np.sin(angles)).flatten() z = function_z(x, y) # Now create the Triangulation . # (Creating a Triangulation without specifying the triangles results in the # Delaunay triangulation of the points.) triang = tri.Triangulation(x, y) # Mask off unwanted triangles. triang.set_mask(np.hypot subdiv=3) #----------------------------------------------------------------------------- # Plot the triangulation
#include <CGAL/Exact_predicates_inexact_constructions_kernel.h> #include <CGAL/Regular_triangulation_euclidean_traits _3.h> #include <CGAL/Delaunay_triangulation_2.h> #include <GLUT/GLUT.h> #include <iostream> #include <cmath> typedef CGAL::Exact_predicates_inexact_constructions_kernel K; typedef CGAL::Delaunay_triangulation glVertex2i( iter->hx(), iter->hy() ); glEnd(); glPopMatrix(); glutSwapBuffers(); } void points_triangulation points_draw(); } if ( button == GLUT_RIGHT_BUTTON && state == GLUT_UP ) points_triangulation
#include <CGAL/Exact_predicates_inexact_constructions_kernel.h> #include <CGAL/Constrained_Delaunay_triangulation Delaunay_mesh_size_criteria_2.h> typedef CGAL::Exact_predicates_inexact_constructions_kernel K; typedef CGAL::Triangulation_vertex_base _2<K> Vb; typedef CGAL::Delaunay_mesh_face_base_2<K> Fb; typedef CGAL::Triangulation_data_structure_2 <Vb, Fb> Tds; typedef CGAL::Constrained_Delaunay_triangulation_2<K, Tds> CDT; typedef CGAL::Delaunay_mesh_size_criteria cout << "Number of vertices: " << cdt.number_of_vertices() <<std::endl; std::cout << "Meshing the triangulation
ActionScript 3 A week or so back I wrote about a package I ported/modified to create the Delaunay triangulation a cool usage of Delaunay triangulation, see my isolining package for ActionScript 3 ? The Delaunay triangulation was invented in 1934 by Boris Delaunay. The port was easy, and makes it a cinch to create a triangulation of, say, selected weather stations Triangulation subroutine 13. Takes as input NV vertices in array pxyz 14.
#include <CGAL/Exact_predicates_inexact_constructions_kernel.h> #include <CGAL/Constrained_Delaunay_triangulation Vb; typedef CGAL::Delaunay_mesh_face_base_2<K> Fb; typedef CGAL::Triangulation_data_structure _2<Vb, Fb> Tds; typedef CGAL::Constrained_Delaunay_triangulation_2<K, Tds> CDT; typedef Point_2( 0, 0)); size_t numTestPoints = points2D.size(); // Create a constrained delaunay triangulation
近日,卡巴斯基安全研究人员Boris Larin披露了iPhone历史上最复杂的间谍软件攻击——三角测量(Triangulation)的技术细节。 自2019年以来,“三角定位行动”(Operation Triangulation)间谍软件持续对iPhone设备进行攻击。该软件利用苹果芯片中未记录的特性绕过基于硬件的安全保护措施。 三角测量操作 Operation Triangulation 是一个针对 Apple iPhone 设备的间谍软件活动,同时利用了四个零日漏洞。 https://www.bleepingcomputer.com/news/security/iphone-triangulation-attack-abused-undocumented-hardware-feature / https://therecord.media/operation-triangulation-iphone-spyware-unknown-hardware-feature
现在我们回过头来解读第七讲最后一个程序:triangulation.cpp。 这里,只有triangulation函数是一个新面孔,在这里阅读以下形参信息,可以预测其功能是通过已知的特征点2d坐标与特征点配对信息,以及刚求解得到的相机位姿变化,来求取特征点的3d坐标。 = 3 ) { cout<<"usage: triangulation img1 img2"<<endl; return 1; } //-- 读取图像 接下来我们来看一下子函数triangulation的定义。 void triangulation ( const vector< KeyPoint >& keypoint_1, const vector< KeyPoint >& keypoint
Heat_method_3/include INCLUDEPATH += $$PWD/Homogeneous_kernel/include INCLUDEPATH += $$PWD/Hyperbolic_triangulation Optimisation_basic/include INCLUDEPATH += $$PWD/Partition_2/include INCLUDEPATH += $$PWD/Periodic_2_triangulation _2/include INCLUDEPATH += $$PWD/Periodic_3_mesh_3/include INCLUDEPATH += $$PWD/Periodic_3_triangulation _3/include INCLUDEPATH += $$PWD/Periodic_4_hyperbolic_triangulation_2/include INCLUDEPATH += $$PWD/Point_set /include INCLUDEPATH += $$PWD/Triangulation_2/include INCLUDEPATH += $$PWD/Triangulation_3/include INCLUDEPATH
;Nef_3;Nef_S2;Number_types;OpenNL;Operations_on_polyhedra;Optimisation_basic;Partition_2;Periodic_2_triangulation _2;Periodic_3_triangulation_3;Point_set_2;Point_set_processing_3;Polygon;Polyhedron;Polyhedron_IO;Polynomial Surface_mesh_segmentation;Surface_mesh_simplification;Surface_mesher;Surface_reconstruction_points_3;Testsuite;Triangulation _2;Triangulation_3;Union_find;Voronoi_diagram_2;kdtree;wininst == Setting paths (DONE) == == Generate
trimesh(tri, x, y, z); % 使用三角网格绘制3D曲面xlabel('X-axis');ylabel('Y-axis');zlabel('Z-axis');title('Delaunay Triangulation ,2), points(:,3)); % 使用三角网格绘制3D曲面xlabel('X-axis');ylabel('Y-axis');zlabel('Z-axis');title('Delaunay Triangulation trimesh(tri, x, y, z); % 使用三角网格绘制3D曲面xlabel('X-axis');ylabel('Y-axis');zlabel('Z-axis');title('Delaunay Triangulation
由于相机的像素是有大小的,一般是几个微米;线激光也是有厚度的,一般也有几个微米到几十微米;triangulation 的结果就不是一个点,而是一个四边形。 我们把这个四边形的纵深称为 triangulation uncertainty. 由于 Triangulation uncertainty 的存在,原本我们设定在 3.8 米处的 planar curtain,变成了一个有一定厚度的 curtain。 巧的是,Triangulation 可以和 phase 相结合,triangulation 可以帮助做 phase unwrapping。 这是因为虽然 triangulation 的 uncertainty 比较高,但也提供了一定的深度信息。所以依然可以得到非常薄的 curtain。 ?
With this purpose in mind, we have the Delaunay triangulation of a set of vertices. The triangles in this triangulation are not necessarily Delaunay. The first example is that of the constrained Delaunay triangulation (cndt). The next step is the computation of a conforming Delaunay triangulation (cfdt). By a path in this setting, we mean a chain of edges of the triangulation.
Exact_predicates_inexact_constructions_kernel.h> #include <CGAL/Projection_traits_xy_3.h> #include <CGAL/Delaunay_triangulation _2.h> #include <CGAL/Triangulation_vertex_base_with_info_2.h> #include <CGAL/Triangulation_face_base_with_info _2.h> #include <CGAL/boost/graph/graph_traits_Delaunay_triangulation_2.h> #include <CGAL/boost/graph/ ; using Segment_3 = Kernel::Segment_3; // Triangulated Irregular Network using TIN = CGAL::Delaunay_triangulation
通过CGAL,我们可以直接通过离散点集生成Delaunay三角网,实现代码如下: #include <CGAL/Delaunay_triangulation_2.h> #include <CGAL/Exact_predicates_inexact_constructions_kernel.h Exact_predicates_inexact_constructions_kernel K; typedef CGAL::Projection_traits_xy_3<K> Gt; typedef CGAL::Delaunay_triangulation Exact_predicates_inexact_constructions_kernel K; typedef CGAL::Projection_traits_xy_3<K> Gt; typedef CGAL::Delaunay_triangulation 最后将该类型作为模板参数传入到Delaunay三角网构建类中:typedef CGAL::Delaunay_triangulation_2<Gt> Delaunay;。
Sampling-based triangulation。 Colmap中提出了一种高效的,sampling-based triangulation方法。 Bundler[3]中对track中的所有匹配对进行triangulation,然后检查是否至少有一个匹配对具有足够大的triangulation angle。 只要找到了这样一对匹配,则对该track中的所有匹配进行triangulation。但是这种方法不够鲁棒,而且计算时间也很长。 Colmap则在triangulation的基础上加上了RANSAC来解决解决任意的outlier ratio的问题。