CGAL 简介
CGAL，Computational Geometry Algorithms Library，
官方主页：http://www.cgal.org/
目前最新版本：CGAL-4.4
计算几何算法开源库的设计目标是，以C++库的形式，提供方便，高效，可靠的几何算法。CGAL可用于各种需要几何计算的领域，如计算机图形学，科学可视化，计算机辅助设计和建模，地理信息系统，分子生物学，医学成像，机器人运动规划，网格生成，数值方法……更高请查看官方主页（http://www.cgal.org/）。
The goal of the CGAL Open Source Project is to provide easy access to efficient and reliable geometric algorithms in the form of a C++ library. CGAL is used in various areas needing geometric computation, such as: computer graphics, scientific visualization, computer aided design and modeling, geographic information systems, molecular biology, medical imaging, robotics and motion planning, mesh generation, numerical methods... More on the projects using CGAL web page.
计算几何算法库（CGAL），提供计算几何相关的数据结构和算法，诸如三角剖分（2D约束三角剖分及二维和三维Delaunay三角剖分），Voronoi图（二维和三维的点，2D加权Voronoi图，分割Voronoi图等），多边形（布尔操作，偏置），多面体（布尔运算），曲线整理及其应用，网格生成（二维Delaunay网格生成和三维表面和体积网格生成等），几何处理（表面网格简化，细分和参数化等），凸壳算法（2D，3D和dD），搜索结构（近邻搜索，kd树等），插值，形状分析，拟合，距离等。
The Computational Geometry Algorithms Library (CGAL), offers data structures and algorithms like triangulations (2D constrained triangulations, and Delaunay triangulations and periodic triangulations in 2D and 3D), Voronoi diagrams(for 2D and 3D points, 2D additively weighted Voronoi diagrams, and segment Voronoi diagrams), polygons (Boolean operations, offsets, straight skeleton), polyhedra (Boolean operations), arrangements of curves and their applications(2D and 3D envelopes, Minkowski sums), mesh generation (2D Delaunay mesh generation and 3D surface and volume mesh generation, skin surfaces), geometry processing (surface mesh simplification, subdivision and parameterization, as well as estimation of local differential properties, and approximation of ridges and umbilics), alpha shapes, convex hull algorithms (in 2D, 3D and dD), search structures (kd trees for nearest neighbor search, and range and segment trees), interpolation (natural neighbor interpolation and placement of streamlines), shape analysis, fitting, and distances(smallest enclosing sphere of points or spheres, smallest enclosing ellipsoid of points, principal component analysis), and kinetic data structures.