Point Cloud Library (PCL) 1.12.1
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
47
48//////////////////////////////////////////////////////////////////////////////////////////////
49template <typename PointNT> void
51{
52 const bool is_far_ignored = dist_ignore_ > 0.0f;
53
54 for (int x = 0; x < res_x_; ++x)
55 {
56 const int y_start = x * res_y_ * res_z_;
57
58 for (int y = 0; y < res_y_; ++y)
59 {
60 const int z_start = y_start + y * res_z_;
61
62 for (int z = 0; z < res_z_; ++z)
63 {
64 pcl::Indices nn_indices (1, 0);
65 std::vector<float> nn_sqr_dists (1, 0.0f);
66 const Eigen::Vector3f point = (lower_boundary_ + size_voxel_ * Eigen::Array3f (x, y, z)).matrix ();
67 PointNT p;
68
69 p.getVector3fMap () = point;
70
71 tree_->nearestKSearch (p, 1, nn_indices, nn_sqr_dists);
72
73 if (!is_far_ignored || nn_sqr_dists[0] < dist_ignore_)
74 {
75 const Eigen::Vector3f normal = (*input_)[nn_indices[0]].getNormalVector3fMap ();
76
77 if (!std::isnan (normal (0)) && normal.norm () > 0.5f)
78 grid_[z_start + z] = normal.dot (
79 point - (*input_)[nn_indices[0]].getVector3fMap ());
80 }
81 }
82 }
83 }
84}
85
86
87
88#define PCL_INSTANTIATE_MarchingCubesHoppe(T) template class PCL_EXPORTS pcl::MarchingCubesHoppe<T>;
89
90#endif // PCL_SURFACE_IMPL_MARCHING_CUBES_HOPPE_H_
91
void voxelizeData() override
Convert the point cloud into voxel data.
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133