Point Cloud Library (PCL)  1.9.1
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 #include <pcl/common/common.h>
41 #include <pcl/common/vector_average.h>
42 #include <pcl/Vertices.h>
43 #include <pcl/kdtree/kdtree_flann.h>
44 
45 //////////////////////////////////////////////////////////////////////////////////////////////
46 template <typename PointNT>
48 {
49 }
50 
51 
52 //////////////////////////////////////////////////////////////////////////////////////////////
53 template <typename PointNT> void
55 {
56  const bool is_far_ignored = dist_ignore_ > 0.0f;
57 
58  for (int x = 0; x < res_x_; ++x)
59  {
60  const int y_start = x * res_y_ * res_z_;
61 
62  for (int y = 0; y < res_y_; ++y)
63  {
64  const int z_start = y_start + y * res_z_;
65 
66  for (int z = 0; z < res_z_; ++z)
67  {
68  std::vector<int> nn_indices (1, 0);
69  std::vector<float> nn_sqr_dists (1, 0.0f);
70  const Eigen::Vector3f point = (lower_boundary_ + size_voxel_ * Eigen::Array3f (x, y, z)).matrix ();
71  PointNT p;
72 
73  p.getVector3fMap () = point;
74 
75  tree_->nearestKSearch (p, 1, nn_indices, nn_sqr_dists);
76 
77  if (!is_far_ignored || nn_sqr_dists[0] < dist_ignore_)
78  {
79  const Eigen::Vector3f normal = input_->points[nn_indices[0]].getNormalVector3fMap ();
80 
81  if (!std::isnan (normal (0)) && normal.norm () > 0.5f)
82  grid_[z_start + z] = normal.dot (
83  point - input_->points[nn_indices[0]].getVector3fMap ());
84  }
85  }
86  }
87  }
88 }
89 
90 
91 
92 #define PCL_INSTANTIATE_MarchingCubesHoppe(T) template class PCL_EXPORTS pcl::MarchingCubesHoppe<T>;
93 
94 #endif // PCL_SURFACE_IMPL_MARCHING_CUBES_HOPPE_H_
95 
common.h
pcl::MarchingCubesHoppe::~MarchingCubesHoppe
~MarchingCubesHoppe()
Destructor.
Definition: marching_cubes_hoppe.hpp:47
pcl::MarchingCubesHoppe::voxelizeData
void voxelizeData()
Convert the point cloud into voxel data.
Definition: marching_cubes_hoppe.hpp:54