Point Cloud Library (PCL)  1.12.1-dev
crh.hpp
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40 
41 #ifndef PCL_FEATURES_IMPL_CRH_H_
42 #define PCL_FEATURES_IMPL_CRH_H_
43 
44 #include <pcl/features/crh.h>
45 #include <pcl/common/fft/kiss_fftr.h>
46 #include <pcl/common/transforms.h>
47 
48 //////////////////////////////////////////////////////////////////////////////////////////////
49 template<typename PointInT, typename PointNT, typename PointOutT>
50 void
52 {
53  // Check if input was set
54  if (!normals_)
55  {
56  PCL_ERROR ("[pcl::%s::computeFeature] No input dataset containing normals was given!\n", getClassName ().c_str ());
57  output.width = output.height = 0;
58  output.clear ();
59  return;
60  }
61 
62  if (normals_->size () != surface_->size ())
63  {
64  PCL_ERROR ("[pcl::%s::computeFeature] The number of points in the input dataset differs from the number of points in the dataset containing the normals!\n", getClassName ().c_str ());
65  output.width = output.height = 0;
66  output.clear ();
67  return;
68  }
69 
70  Eigen::Vector3f plane_normal;
71  plane_normal[0] = -centroid_[0];
72  plane_normal[1] = -centroid_[1];
73  plane_normal[2] = -centroid_[2];
74  Eigen::Vector3f z_vector = Eigen::Vector3f::UnitZ ();
75  plane_normal.normalize ();
76  Eigen::Vector3f axis = plane_normal.cross (z_vector);
77  double rotation = -asin (axis.norm ());
78  axis.normalize ();
79 
80  int nbins = nbins_;
81  int bin_angle = 360 / nbins;
82 
83  Eigen::Affine3f transformPC (Eigen::AngleAxisf (static_cast<float> (rotation), axis));
84 
86  grid.resize (indices_->size ());
87 
88  for (std::size_t i = 0; i < indices_->size (); i++)
89  {
90  grid[i].getVector4fMap () = (*surface_)[(*indices_)[i]].getVector4fMap ();
91  grid[i].getNormalVector4fMap () = (*normals_)[(*indices_)[i]].getNormalVector4fMap ();
92  }
93 
94  pcl::transformPointCloudWithNormals (grid, grid, transformPC);
95 
96  //fill spatial data vector and the zero-initialize or "value-initialize" an array on c++,
97  // the initialization is made with () after the [nbins]
98  std::vector<kiss_fft_scalar> spatial_data(nbins);
99 
100  float sum_w = 0;
101  for (const auto &point : grid.points)
102  {
103  int bin = static_cast<int> ((((std::atan2 (point.normal_y, point.normal_x) + M_PI) * 180 / M_PI) / bin_angle)) % nbins;
104  float w = std::sqrt (point.normal_y * point.normal_y + point.normal_x * point.normal_x);
105  sum_w += w;
106  spatial_data[bin] += w;
107  }
108 
109  for (auto& data: spatial_data)
110  data /= sum_w;
111 
112  std::vector<kiss_fft_cpx> freq_data(nbins / 2 + 1);
113  kiss_fftr_cfg mycfg = kiss_fftr_alloc (nbins, 0, nullptr, nullptr);
114  kiss_fftr (mycfg, spatial_data.data (), freq_data.data ());
115 
116  for (auto& data: freq_data)
117  {
118  data.r /= freq_data[0].r;
119  data.i /= freq_data[0].r;
120  }
121 
122  output.resize (1);
123  output.width = output.height = 1;
124 
125  output[0].histogram[0] = freq_data[0].r; //dc
126  int k = 1;
127  for (int i = 1; i < (nbins / 2); i++, k += 2)
128  {
129  output[0].histogram[k] = freq_data[i].r;
130  output[0].histogram[k + 1] = freq_data[i].i;
131  }
132 
133  output[0].histogram[nbins - 1] = freq_data[nbins / 2].r; //nyquist
134 }
135 
136 #define PCL_INSTANTIATE_CRHEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::CRHEstimation<T,NT,OutT>;
137 
138 #endif // PCL_FEATURES_IMPL_CRH_H_
CRHEstimation estimates the Camera Roll Histogram (CRH) descriptor for a given point cloud dataset co...
Definition: crh.h:61
void resize(std::size_t count)
Resizes the container to contain count elements.
Definition: point_cloud.h:462
std::vector< PointT, Eigen::aligned_allocator< PointT > > points
The point data.
Definition: point_cloud.h:395
void transformPointCloudWithNormals(const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields)
Transform a point cloud and rotate its normals using an Eigen transform.
Definition: transforms.hpp:349
#define M_PI
Definition: pcl_macros.h:201