Point Cloud Library (PCL)  1.8.1
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  : MarchingCubes<PointNT> ()
49 {
50 }
51 
52 //////////////////////////////////////////////////////////////////////////////////////////////
53 template <typename PointNT>
55 {
56 }
57 
58 
59 //////////////////////////////////////////////////////////////////////////////////////////////
60 template <typename PointNT> void
62 {
63  for (int x = 0; x < res_x_; ++x)
64  for (int y = 0; y < res_y_; ++y)
65  for (int z = 0; z < res_z_; ++z)
66  {
67  std::vector<int> nn_indices;
68  std::vector<float> nn_sqr_dists;
69 
70  Eigen::Vector3f point;
71  point[0] = min_p_[0] + (max_p_[0] - min_p_[0]) * float (x) / float (res_x_);
72  point[1] = min_p_[1] + (max_p_[1] - min_p_[1]) * float (y) / float (res_y_);
73  point[2] = min_p_[2] + (max_p_[2] - min_p_[2]) * float (z) / float (res_z_);
74 
75  PointNT p;
76  p.getVector3fMap () = point;
77 
78  tree_->nearestKSearch (p, 1, nn_indices, nn_sqr_dists);
79 
80  grid_[x * res_y_*res_z_ + y * res_z_ + z] = input_->points[nn_indices[0]].getNormalVector3fMap ().dot (
81  point - input_->points[nn_indices[0]].getVector3fMap ());
82  }
83 }
84 
85 
86 
87 #define PCL_INSTANTIATE_MarchingCubesHoppe(T) template class PCL_EXPORTS pcl::MarchingCubesHoppe<T>;
88 
89 #endif // PCL_SURFACE_IMPL_MARCHING_CUBES_HOPPE_H_
90 
The marching cubes surface reconstruction algorithm.
void voxelizeData()
Convert the point cloud into voxel data.
Define standard C methods and C++ classes that are common to all methods.