CGALApps

Collection of small self-contained one-task programs designed to easily apply CGAL algorithms to data sets and combine these algorithms using standard Unix pipes.

Documentation

All applications embed their own documentation accessible with the argument --help (or -h). For example:

$ cgal_efficient_ransac --help
---------------------------
[CGALApps] Efficient RANSAC
---------------------------

Efficient RANSAC algorithm to detect shapes in a point set.

Options:
  -h [ --help ]                         Display this help message
  -v [ --verbose ]                      Display info to stderr
  -i [ --input ] arg (=stdin)           Input file
  -o [ --output ] arg (=stdout)         Output file in PLY format
  -p [ --probability ] arg (=0.050000)  Probability for search endurance
  -m [ --min-points ] arg (=1% of total diagonal)
                                        Minimum number of points in shape
  -e [ --epsilon ] arg (=1% of bounding box diagonal)
                                        Maximum tolerance from point to shape
  -n [ --normal ] arg (=0.450000)       Maximum normal deviation in radiants
  -c [ --cluster ] arg (=1% of bounding box diagonal)
                                        Maximum distances between connected 
                                        points

Shapes:
  -P [ --planes ]                       Detect planes
  -C [ --cylinders ]                    Detect cylinders
  -N [ --cones ]                        Detect cones
  -T [ --torus ]                        Detect torues
  -S [ --spheres ]                      Detect spheres

For more information on the parameters, please refer to the corresponding CGAL reference manual pages.

Examples

To compute the average spacing using 6 nearest neighbors (default):

$ cgal_compute_average_spacing data/example.xyz
0.048374

To compute the average spacing using 12 nearest neighbors:

$ cgal_compute_average_spacing data/example.xyz -n 12
0.072842

To simplify a point set using a regular grid of size 0.5:

$ cgal_grid_simplify_point_set data/example.xyz -e 0.5 -o out.ply

To reconstruct a simplified version of a point set:

$ cgal_grid_simplify_point_set data/example.xyz -e 0.5 | cgal_advancing_front_surface_reconstruction -o reco.off

Available Apps

• cgal_advancing_front_surface_reconstruction
• cgal_cluster_point_set
• cgal_compute_average_spacing
• cgal_convert
• cgal_efficient_ransac
• cgal_grid_simplify_point_set
• cgal_jet_estimate_normals
• cgal_jet_smooth_point_set
• cgal_mst_orient_normals
• cgal_poisson_surface_reconstruction
• cgal_random_simplify_point_set
• cgal_remove_outliers
• cgal_scale_space_surface_reconstruction

Todo

Point Set Processing

• estimate_k_neighbor_scale()
• estimate_range_scale()
• hierarchy_simplify_point_set()
• wlop_simplify_and_regularize_point_set()
• bilateral_point_set()
• pca_estimate_normals()
• edge_aware_upsample_point_set()
• vcm_estimate_normals()
• structure_point_set()