Trouble when using Efficient_Ransac in CGAL - c++

Question

I want to use the Efficient Ransac implementation of CGAL, but whenever I try to set my own parameters, the algorithm doesn't detect any shape anymore.
This work is related to the Polyfit implementation in CGAL. I want to fine tune the plane detection to see the influence it has on the algorithm. When I use the standard call to ransac.detect(), it works perfectly. However, when I want to set my own parameters it just doesn't find any plane, even if I set them manually to the default values.
Here is my code, strongly related to this example
#include <CGAL/Exact_predicates_inexact_constructions_kernel.h>
#include <CGAL/IO/read_xyz_points.h>
#include <CGAL/IO/Writer_OFF.h>
#include <CGAL/property_map.h>
#include <CGAL/Surface_mesh.h>
#include <CGAL/Shape_detection/Efficient_RANSAC.h>
#include <CGAL/Polygonal_surface_reconstruction.h>
#ifdef CGAL_USE_SCIP
#include <CGAL/SCIP_mixed_integer_program_traits.h>
typedef CGAL::SCIP_mixed_integer_program_traits<double> MIP_Solver;
#elif defined(CGAL_USE_GLPK)
#include <CGAL/GLPK_mixed_integer_program_traits.h>
typedef CGAL::GLPK_mixed_integer_program_traits<double> MIP_Solver;
#endif
#if defined(CGAL_USE_GLPK) || defined(CGAL_USE_SCIP)
#include <CGAL/Timer.h>
#include <fstream>
typedef CGAL::Exact_predicates_inexact_constructions_kernel Kernel;
typedef Kernel::Point_3 Point;
typedef Kernel::Vector_3 Vector;
// Point with normal, and plane index
typedef boost::tuple<Point, Vector, int> PNI;
typedef std::vector<PNI> Point_vector;
typedef CGAL::Nth_of_tuple_property_map<0, PNI> Point_map;
typedef CGAL::Nth_of_tuple_property_map<1, PNI> Normal_map;
typedef CGAL::Nth_of_tuple_property_map<2, PNI> Plane_index_map;
typedef CGAL::Shape_detection::Efficient_RANSAC_traits<Kernel, Point_vector, Point_map, Normal_map> Traits;
typedef CGAL::Shape_detection::Efficient_RANSAC<Traits> Efficient_ransac;
typedef CGAL::Shape_detection::Plane<Traits> Plane;
typedef CGAL::Shape_detection::Point_to_shape_index_map<Traits> Point_to_shape_index_map;
typedef CGAL::Polygonal_surface_reconstruction<Kernel> Polygonal_surface_reconstruction;
typedef CGAL::Surface_mesh<Point> Surface_mesh;
int main(int argc, char ** argv)
{
Point_vector points;
// Loads point set from a file.
const std::string &input_file = argv[1];
//const std::string input_file(input);
std::ifstream input_stream(input_file.c_str());
if (input_stream.fail()) {
std::cerr << "failed open file \'" <<input_file << "\'" << std::endl;
return EXIT_FAILURE;
}
std::cout << "Loading point cloud: " << input_file << "...";
CGAL::Timer t;
t.start();
if (!input_stream ||
!CGAL::read_xyz_points(input_stream,
std::back_inserter(points),
CGAL::parameters::point_map(Point_map()).normal_map(Normal_map())))
{
std::cerr << "Error: cannot read file " << input_file << std::endl;
return EXIT_FAILURE;
}
else
std::cout << " Done. " << points.size() << " points. Time: " << t.time() << " sec." << std::endl;
// Shape detection
Efficient_ransac ransac;
ransac.set_input(points);
ransac.add_shape_factory<Plane>();
std::cout << "Extracting planes...";
t.reset();
// Set parameters for shape detection.
Efficient_ransac::Parameters parameters;
// Set probability to miss the largest primitive at each iteration.
parameters.probability = 0.05;
// Detect shapes with at least 500 points.
parameters.min_points = 100;
// Set maximum Euclidean distance between a point and a shape.
parameters.epsilon = 0.01;
// Set maximum Euclidean distance between points to be clustered.
parameters.cluster_epsilon = 0.01;
// Set maximum normal deviation.
// 0.9 < dot(surface_normal, point_normal);
parameters.normal_threshold = 0.9;
// Detect shapes.
ransac.detect(parameters);
//ransac.detect();
Efficient_ransac::Plane_range planes = ransac.planes();
std::size_t num_planes = planes.size();
std::cout << " Done. " << num_planes << " planes extracted. Time: " << t.time() << " sec." << std::endl;
// Stores the plane index of each point as the third element of the tuple.
Point_to_shape_index_map shape_index_map(points, planes);
for (std::size_t i = 0; i < points.size(); ++i) {
// Uses the get function from the property map that accesses the 3rd element of the tuple.
int plane_index = get(shape_index_map, i);
points[i].get<2>() = plane_index;
}
//////////////////////////////////////////////////////////////////////////
std::cout << "Generating candidate faces...";
t.reset();
Polygonal_surface_reconstruction algo(
points,
Point_map(),
Normal_map(),
Plane_index_map()
);
std::cout << " Done. Time: " << t.time() << " sec." << std::endl;
//////////////////////////////////////////////////////////////////////////
Surface_mesh model;
std::cout << "Reconstructing...";
t.reset();
if (!algo.reconstruct<MIP_Solver>(model)) {
std::cerr << " Failed: " << algo.error_message() << std::endl;
return EXIT_FAILURE;
}
const std::string& output_file(input_file+"_result.off");
std::ofstream output_stream(output_file.c_str());
if (output_stream && CGAL::write_off(output_stream, model))
std::cout << " Done. Saved to " << output_file << ". Time: " << t.time() << " sec." << std::endl;
else {
std::cerr << " Failed saving file." << std::endl;
return EXIT_FAILURE;
}
//////////////////////////////////////////////////////////////////////////
// Also stores the candidate faces as a surface mesh to a file
Surface_mesh candidate_faces;
algo.output_candidate_faces(candidate_faces);
const std::string& candidate_faces_file(input_file+"_candidate_faces.off");
std::ofstream candidate_stream(candidate_faces_file.c_str());
if (candidate_stream && CGAL::write_off(candidate_stream, candidate_faces))
std::cout << "Candidate faces saved to " << candidate_faces_file << "." << std::endl;
return EXIT_SUCCESS;
}
#else
int main(int, char**)
{
std::cerr << "This test requires either GLPK or SCIP.\n";
return EXIT_SUCCESS;
}
#endif // defined(CGAL_USE_GLPK) || defined(CGAL_USE_SCIP)
When launched, I have the following message:
Loading point cloud: Scene1/test.xyz... Done. 169064 points. Time: 0.428 sec.
Extracting planes... Done. 0 planes extracted. Time: 8.328 sec.
Generating candidate faces... Done. Time: 0.028 sec.
Reconstructing... Failed: at least 4 planes required to reconstruct a closed surface mesh (only 1 provided)
While I have this when launching the code the ransac detection function without parameters:
Loading point cloud: Scene1/test.xyz... Done. 169064 points. Time: 0.448 sec.
Extracting planes... Done. 18 planes extracted. Time: 3.088 sec.
Generating candidate faces... Done. Time: 94.536 sec.
Reconstructing... Done. Saved to Scene1/test.xyz_result.off. Time: 30.28 sec.
Can someone help me setting my own parameters for the ransac shape detection?

Answer 1

However, when I want to set my own parameters it just doesn't find any
plane, even if I set them manually to the default values.
Just to be sure: "setting them manually to the default values" is not what you are doing in the code you shared.
Default values are documented as:
1% of the total number of points for min_points, which should be around 1700 points in your case, not 100
1% of the bounding box diagonal for epsilon and cluster_epsilon. For that obviously I don't know if that is what you used (0.01) as I don't have access to your point set, but if you want to reproduce default values, you should use the CGAL::Bbox_3 object at some point
If you use these values, there's no reason why it should behave differently than with no parameters given (if it does not work, then please let me know because there may be a bug).