CGAL Classification Package Given a point cloud and a user-defined set of classes (e.g. vegetation, ground, roofs, etc.), the algorithm classifies the points by computing a set of geometric attributes and minimizing a globally regularized…

3D surface reconstruction of laser scanned terrestrial objects like rock formations and tunnels. Excess points are skipped by entering a parameter of resulting accuracy requirement, given by max distance from resulting surface to points in…

Given a closed triangulated surface mesh, the algorithm iteratively contracts the surface mesh along the surface mean curvature flow until convergence. A 1D skeleton is then extracted from the contracted surface. The skeleton encodes the…

Given a triangulated surface mesh as input and a set of source points on the mesh, the algorithm computes a data structure that can efficiently answer shortest path queries from any point on the mesh…

Given two input surface meshes (not necessarily triangulated) representing the same model, this component produces a third triangle mesh where each face of each input mesh is represented by a collection of faces of the…

Based on the CGAL 3D Meshing Generation package an extension has been developed that allows to automatically create tetrahedral grids suitable for finite element analysis. This work is part of the European project MXL, ICT-2009.5.2.

Intergraph’s LPS, a complete suite of photogrammetric production tools, uses the CGAL 2D Delaunay triangulation to perform terrain segmentation, building footprint delineation, and terrain classification on LiDAR point clouds.