read xyz, compute normal, orient, and Poisson reconstruction

poisson.cpp

#include <CGAL/trace.h>
#include <CGAL/Exact_predicates_inexact_constructions_kernel.h>
#include <CGAL/Polyhedron_3.h>
#include <CGAL/IO/Polyhedron_iostream.h>
#include <CGAL/Surface_mesh_default_triangulation_3.h>
#include <CGAL/make_surface_mesh.h>
#include <CGAL/Implicit_surface_3.h>
#include <CGAL/IO/output_surface_facets_to_polyhedron.h>
#include <CGAL/Poisson_reconstruction_function.h>
#include <CGAL/Point_with_normal_3.h>
#include <CGAL/property_map.h>
#include <CGAL/IO/read_xyz_points.h>
#include <CGAL/compute_average_spacing.h>
#include <CGAL/jet_estimate_normals.h>
#include <CGAL/mst_orient_normals.h>

#include <CGAL/Polygon_mesh_processing/distance.h>

#include <vector>
#include <fstream>

#ifdef CGAL_LINKED_WITH_TBB
typedef CGAL::Parallel_tag Concurrency_tag;
#else
typedef CGAL::Sequential_tag Concurrency_tag;
#endif

// Types
typedef CGAL::Exact_predicates_inexact_constructions_kernel Kernel;
typedef Kernel::FT FT;
typedef Kernel::Point_3 Point;
typedef CGAL::Point_with_normal_3<Kernel> Point_with_normal;
typedef Kernel::Sphere_3 Sphere;
typedef std::vector<Point_with_normal> PointList;
typedef CGAL::Polyhedron_3<Kernel> Polyhedron;
typedef CGAL::Poisson_reconstruction_function<Kernel> Poisson_reconstruction_function;
typedef CGAL::Surface_mesh_default_triangulation_3 STr;
typedef CGAL::Surface_mesh_complex_2_in_triangulation_3<STr> C2t3;
typedef CGAL::Implicit_surface_3<Kernel, Poisson_reconstruction_function> Surface_3;

int main(void)
{
    // Poisson options
    FT sm_angle = 20.0; // Min triangle angle in degrees.
    FT sm_radius = 30; // Max triangle size w.r.t. point set average spacing.
    FT sm_distance = 0.375; // Surface Approximation error w.r.t. point set average spacing.

    // Reads the point set file in points[].
    // Note: read_xyz_points_and_normals() requires an iterator over points
    // + property maps to access each point's position and normal.
    // The position property map can be omitted here as we use iterators over Point_3 elements.
    PointList points;
    std::ifstream stream("data/kitten.xyz");
    if (!stream ||
        !CGAL::read_xyz_points(
                              stream,
                              std::back_inserter(points)))
    {
      std::cerr << "Error: cannot read file data/kitten.xyz" << std::endl;
      return EXIT_FAILURE;
    }

    const int nb_neighbors = 18; 

    CGAL::jet_estimate_normals<Concurrency_tag>(
                                                points.begin(), points.end(),
                                                CGAL::Identity_property_map<Point>(),
                                                CGAL::make_normal_of_point_with_normal_pmap(PointList::value_type()),
                                                nb_neighbors);

 PointList::iterator unoriented_points_begin =
    CGAL::mst_orient_normals(points.begin(), points.end(),
                             CGAL::Identity_property_map<Point>(),
                             CGAL::make_normal_of_point_with_normal_pmap(PointList::value_type()),
                             nb_neighbors);

    // Creates implicit function from the read points using the default solver.

    // Note: this method requires an iterator over points
    // + property maps to access each point's position and normal.
    // The position property map can be omitted here as we use iterators over Point_3 elements.
    Poisson_reconstruction_function function(points.begin(), unoriented_points_begin,
                                             CGAL::make_normal_of_point_with_normal_pmap(PointList::value_type()) );

    // Computes the Poisson indicator function f()
    // at each vertex of the triangulation.
    if ( ! function.compute_implicit_function() ) 
      return EXIT_FAILURE;

    // Computes average spacing
    FT average_spacing = CGAL::compute_average_spacing<CGAL::Sequential_tag>(points.begin(), points.end(),
                                                       6 /* knn = 1 ring */);

    // Gets one point inside the implicit surface
    // and computes implicit function bounding sphere radius.
    Point inner_point = function.get_inner_point();
    Sphere bsphere = function.bounding_sphere();
    FT radius = std::sqrt(bsphere.squared_radius());

    // Defines the implicit surface: requires defining a
    // conservative bounding sphere centered at inner point.
    FT sm_sphere_radius = 5.0 * radius;
    FT sm_dichotomy_error = sm_distance*average_spacing/1000.0; // Dichotomy error must be << sm_distance
    Surface_3 surface(function,
                      Sphere(inner_point,sm_sphere_radius*sm_sphere_radius),
                      sm_dichotomy_error/sm_sphere_radius);

    // Defines surface mesh generation criteria
    CGAL::Surface_mesh_default_criteria_3<STr> criteria(sm_angle,  // Min triangle angle (degrees)
                                                        sm_radius*average_spacing,  // Max triangle size
                                                        sm_distance*average_spacing); // Approximation error

    // Generates surface mesh with manifold option
    STr tr; // 3D Delaunay triangulation for surface mesh generation
    C2t3 c2t3(tr); // 2D complex in 3D Delaunay triangulation
    CGAL::make_surface_mesh(c2t3,                                 // reconstructed mesh
                            surface,                              // implicit surface
                            criteria,                             // meshing criteria
                            CGAL::Manifold_with_boundary_tag());  // require manifold mesh

    if(tr.number_of_vertices() == 0)
      return EXIT_FAILURE;

    // saves reconstructed surface mesh
    std::ofstream out("kitten_poisson-20-30-0.375.off");
    Polyhedron output_mesh;
    CGAL::output_surface_facets_to_polyhedron(c2t3, output_mesh);
    out << output_mesh;


    /// [PMP_distance_snippet]
    // computes the approximation error of the reconstruction
    double max_dist =
      CGAL::Polygon_mesh_processing::approximate_max_distance_to_point_set(output_mesh,
                                                               points,
                                                               4000);
    std::cout << "Max distance to point_set: " << max_dist << std::endl;
    /// [PMP_distance_snippet]

    return EXIT_SUCCESS;
}