CGAL users discussion list

["Sebastien Loriot (GeometryFactory)" <>]

On 02/09/2018 03:41 AM, williamlai3a wrote:
> Hi All,
>
> I am a newbie to CGAL, I am trying code from CGAL github master build
> (v4.12) to do 3D point set processing.
> I am using the following:
> typedef CGAL::Exact_predicates_inexact_constructions_kernel Kernel;
> typedef Kernel::FT FT;
> typedef Kernel::Point_3 Point;
> typedef Kernel::Vector_3 Vector;
> typedef CGAL::Point_set_3<Point> Point_set;
>
> However, in my original .xyz point cloud, I am having high precision like:
> 841293.765978 818818.600281 90.933151
> 841293.765000 818818.599880 90.906294
> 841293.764292 818818.599046 90.960005
> 841284.839693 818813.763807 90.725665
> 841284.822854 818813.767425 90.684145
> 841284.822320 818813.766970 90.696840
> 841284.821787 818813.766515 90.709534
> 841284.825319 818813.768227 90.721745
>
> After processing normal, and I write back the points to a .xyz, the point
> precision becomes:
> 841294 818819 90.9332 0 0 0
> 841294 818819 90.9063 0 0 0
> 841294 818819 90.96 0 0 0
> 841285 818814 90.7257 0 0 0
> 841285 818814 90.6841 0 0 0
> 841285 818814 90.6968 0 0 0
> 841285 818814 90.7095 0 0 0
> 841285 818814 90.7217 0 0 0
>
> Problem 1:
> Seems to me that the output is being trimmed to 6 significant figure.
> Are there any ways to output much higher significant figure, say 12?

6 is the default precision of the stream. You can increase the precision
(the max being 17 if you want to guarantee that a value will be 
identical to the one wrote when you read it).


Try something like:
std::ofstream output("out.xyz");
output << std::setprecision(17);


> Problem 2:
> In my normal reconstruction processing, I am trying to use the following:
> // Computes average spacing.
>      const unsigned int nb_neighbors = 6; // 1 ring
>      FT average_spacing = CGAL::compute_average_spacing<Concurrency_tag>(
>                              point_sets,  // CGAL::Point_set_3<Point>
>                              nb_neighbors,
>                             
> CGAL::parameters::point_map(point_sets.point_map())
>                          );
>
>          point_sets.add_normal_map();
>          CGAL::vcm_estimate_normals(
>              point_sets,
>              CGAL::to_double(average_spacing)*20,
>              CGAL::to_double(average_spacing),
>              CGAL::parameters::point_map(point_sets.point_map()).
>                                normal_map(point_sets.normal_map())
>          );
>
>          Point_set::iterator unoriented_points_begin =
>          CGAL::mst_orient_normals(point_sets,
>                                   nb_neighbors,
>                                  
> CGAL::parameters::point_map(point_sets.point_map()).
>                                                    
> normal_map(point_sets.normal_map())
>          );
>          // Optional: delete points with an unoriented normal
>          // if you plan to call a reconstruction algorithm that expects
> oriented normals.
>          point_sets.remove(unoriented_points_begin, point_sets.end());
>          point_sets.collect_garbage();
>
> As you can see from the above output, all normals are <0 0 0>
> However, my point cloud contains a lot of planar surfaces with different
> orientation.
> Are there any things wrong with my code? Parameter problem? or I am doing in
> a wrong concept way.

It has probably something to do with the parameters.
Did you try `jet_estimate_normals` that is easier to use?
https://doc.cgal.org/latest/Point_set_processing_3/group__PkgPointSetProcessingAlgorithms.html#ga2ab9546e4d0ef01bd8a26e748046b26a

Sebastien.

> Thank you very much in advance for any suggestions and recommendation.
>
> Best regards,
> William
>
>
>
> --
> Sent from: http://cgal-discuss.949826.n4.nabble.com/