Point Cloud Library (PCL) 1.14.0
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marching_cubes_hoppe.hpp
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35
36#ifndef PCL_SURFACE_IMPL_MARCHING_CUBES_HOPPE_H_
37#define PCL_SURFACE_IMPL_MARCHING_CUBES_HOPPE_H_
38
39#include <pcl/surface/marching_cubes_hoppe.h>
40
41//////////////////////////////////////////////////////////////////////////////////////////////
42template <typename PointNT>
44
45
46//////////////////////////////////////////////////////////////////////////////////////////////
47template <typename PointNT> void
49{
50 const bool is_far_ignored = dist_ignore_ > 0.0f;
51
52 for (int x = 0; x < res_x_; ++x)
53 {
54 const int y_start = x * res_y_ * res_z_;
55
56 for (int y = 0; y < res_y_; ++y)
57 {
58 const int z_start = y_start + y * res_z_;
59
60 for (int z = 0; z < res_z_; ++z)
61 {
62 pcl::Indices nn_indices (1, 0);
63 std::vector<float> nn_sqr_dists (1, 0.0f);
64 const Eigen::Vector3f point = (lower_boundary_ + size_voxel_ * Eigen::Array3f (x, y, z)).matrix ();
65 PointNT p;
66
67 p.getVector3fMap () = point;
68
69 tree_->nearestKSearch (p, 1, nn_indices, nn_sqr_dists);
70
71 if (!is_far_ignored || nn_sqr_dists[0] < dist_ignore_)
72 {
73 const Eigen::Vector3f normal = (*input_)[nn_indices[0]].getNormalVector3fMap ();
74
75 if (!std::isnan (normal (0)) && normal.norm () > 0.5f)
76 grid_[z_start + z] = normal.dot (
77 point - (*input_)[nn_indices[0]].getVector3fMap ());
78 }
79 }
80 }
81 }
82}
83
84
85
86#define PCL_INSTANTIATE_MarchingCubesHoppe(T) template class PCL_EXPORTS pcl::MarchingCubesHoppe<T>;
87
88#endif // PCL_SURFACE_IMPL_MARCHING_CUBES_HOPPE_H_
89
~MarchingCubesHoppe() override
Destructor.
void voxelizeData() override
Convert the point cloud into voxel data.
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133