Point Cloud Library (PCL)  1.11.1-dev
3dsc.hpp
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38 
39 #pragma once
40 
41 #include <pcl/features/3dsc.h>
42 
43 #include <pcl/common/angles.h>
44 #include <pcl/common/geometry.h>
45 #include <pcl/common/point_tests.h> // for pcl::isFinite
46 #include <pcl/common/utils.h>
47 
48 #include <cmath>
49 #include <numeric> // for partial_sum
50 
51 //////////////////////////////////////////////////////////////////////////////////////////////
52 template <typename PointInT, typename PointNT, typename PointOutT> bool
54 {
56  {
57  PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
58  return (false);
59  }
60 
61  if (search_radius_< min_radius_)
62  {
63  PCL_ERROR ("[pcl::%s::initCompute] search_radius_ must be GREATER than min_radius_.\n", getClassName ().c_str ());
64  return (false);
65  }
66 
67  // Update descriptor length
68  descriptor_length_ = elevation_bins_ * azimuth_bins_ * radius_bins_;
69 
70  // Compute radial, elevation and azimuth divisions
71  float azimuth_interval = 360.0f / static_cast<float> (azimuth_bins_);
72  float elevation_interval = 180.0f / static_cast<float> (elevation_bins_);
73 
74  // Reallocate divisions and volume lut
75  radii_interval_.clear ();
76  phi_divisions_.clear ();
77  theta_divisions_.clear ();
78  volume_lut_.clear ();
79 
80  // Fills radii interval based on formula (1) in section 2.1 of Frome's paper
81  radii_interval_.resize (radius_bins_ + 1);
82  for (std::size_t j = 0; j < radius_bins_ + 1; j++)
83  radii_interval_[j] = static_cast<float> (std::exp (std::log (min_radius_) + ((static_cast<float> (j) / static_cast<float> (radius_bins_)) * std::log (search_radius_ / min_radius_))));
84 
85  // Fill theta divisions of elevation
86  theta_divisions_.resize (elevation_bins_ + 1, elevation_interval);
87  theta_divisions_[0] = 0.f;
88  std::partial_sum(theta_divisions_.begin (), theta_divisions_.end (), theta_divisions_.begin ());
89 
90  // Fill phi didvisions of elevation
91  phi_divisions_.resize (azimuth_bins_ + 1, azimuth_interval);
92  phi_divisions_[0] = 0.f;
93  std::partial_sum(phi_divisions_.begin (), phi_divisions_.end (), phi_divisions_.begin ());
94 
95  // LookUp Table that contains the volume of all the bins
96  // "phi" term of the volume integral
97  // "integr_phi" has always the same value so we compute it only one time
98  float integr_phi = pcl::deg2rad (phi_divisions_[1]) - pcl::deg2rad (phi_divisions_[0]);
99  // exponential to compute the cube root using pow
100  float e = 1.0f / 3.0f;
101  // Resize volume look up table
102  volume_lut_.resize (radius_bins_ * elevation_bins_ * azimuth_bins_);
103  // Fill volumes look up table
104  for (std::size_t j = 0; j < radius_bins_; j++)
105  {
106  // "r" term of the volume integral
107  float integr_r = (radii_interval_[j+1] * radii_interval_[j+1] * radii_interval_[j+1] / 3.0f) - (radii_interval_[j] * radii_interval_[j] * radii_interval_[j] / 3.0f);
108 
109  for (std::size_t k = 0; k < elevation_bins_; k++)
110  {
111  // "theta" term of the volume integral
112  float integr_theta = std::cos (pcl::deg2rad (theta_divisions_[k])) - std::cos (pcl::deg2rad (theta_divisions_[k+1]));
113  // Volume
114  float V = integr_phi * integr_theta * integr_r;
115  // Compute cube root of the computed volume commented for performance but left
116  // here for clarity
117  // float cbrt = pow(V, e);
118  // cbrt = 1 / cbrt;
119 
120  for (std::size_t l = 0; l < azimuth_bins_; l++)
121  {
122  // Store in lut 1/cbrt
123  //volume_lut_[ (l*elevation_bins_*radius_bins_) + k*radius_bins_ + j ] = cbrt;
124  volume_lut_[(l*elevation_bins_*radius_bins_) + k*radius_bins_ + j] = 1.0f / powf (V, e);
125  }
126  }
127  }
128  return (true);
129 }
130 
131 //////////////////////////////////////////////////////////////////////////////////////////////
132 template <typename PointInT, typename PointNT, typename PointOutT> bool
134  std::size_t index, const pcl::PointCloud<PointNT> &normals, float rf[9], std::vector<float> &desc)
135 {
136  // The RF is formed as this x_axis | y_axis | normal
137  Eigen::Map<Eigen::Vector3f> x_axis (rf);
138  Eigen::Map<Eigen::Vector3f> y_axis (rf + 3);
139  Eigen::Map<Eigen::Vector3f> normal (rf + 6);
140 
141  // Find every point within specified search_radius_
142  std::vector<int> nn_indices;
143  std::vector<float> nn_dists;
144  const std::size_t neighb_cnt = searchForNeighbors ((*indices_)[index], search_radius_, nn_indices, nn_dists);
145  if (neighb_cnt == 0)
146  {
147  std::fill (desc.begin (), desc.end (), std::numeric_limits<float>::quiet_NaN ());
148  std::fill (rf, rf + 9, 0.f);
149  return (false);
150  }
151 
152  const auto minDistanceIt = std::min_element(nn_dists.begin (), nn_dists.end ());
153  const auto minIndex = nn_indices[std::distance (nn_dists.begin (), minDistanceIt)];
154 
155  // Get origin point
156  Vector3fMapConst origin = (*input_)[(*indices_)[index]].getVector3fMap ();
157  // Get origin normal
158  // Use pre-computed normals
159  normal = normals[minIndex].getNormalVector3fMap ();
160 
161  // Compute and store the RF direction
162  x_axis[0] = rnd ();
163  x_axis[1] = rnd ();
164  x_axis[2] = rnd ();
165  if (!pcl::utils::equal (normal[2], 0.0f))
166  x_axis[2] = - (normal[0]*x_axis[0] + normal[1]*x_axis[1]) / normal[2];
167  else if (!pcl::utils::equal (normal[1], 0.0f))
168  x_axis[1] = - (normal[0]*x_axis[0] + normal[2]*x_axis[2]) / normal[1];
169  else if (!pcl::utils::equal (normal[0], 0.0f))
170  x_axis[0] = - (normal[1]*x_axis[1] + normal[2]*x_axis[2]) / normal[0];
171 
172  x_axis.normalize ();
173 
174  // Check if the computed x axis is orthogonal to the normal
175  assert (pcl::utils::equal (x_axis[0]*normal[0] + x_axis[1]*normal[1] + x_axis[2]*normal[2], 0.0f, 1E-6f));
176 
177  // Store the 3rd frame vector
178  y_axis.matrix () = normal.cross (x_axis);
179 
180  // For each point within radius
181  for (std::size_t ne = 0; ne < neighb_cnt; ne++)
182  {
183  if (pcl::utils::equal (nn_dists[ne], 0.0f))
184  continue;
185  // Get neighbours coordinates
186  Eigen::Vector3f neighbour = (*surface_)[nn_indices[ne]].getVector3fMap ();
187 
188  /// ----- Compute current neighbour polar coordinates -----
189  /// Get distance between the neighbour and the origin
190  float r = std::sqrt (nn_dists[ne]);
191 
192  /// Project point into the tangent plane
193  Eigen::Vector3f proj;
194  pcl::geometry::project (neighbour, origin, normal, proj);
195  proj -= origin;
196 
197  /// Normalize to compute the dot product
198  proj.normalize ();
199 
200  /// Compute the angle between the projection and the x axis in the interval [0,360]
201  Eigen::Vector3f cross = x_axis.cross (proj);
202  float phi = pcl::rad2deg (std::atan2 (cross.norm (), x_axis.dot (proj)));
203  phi = cross.dot (normal) < 0.f ? (360.0f - phi) : phi;
204  /// Compute the angle between the neighbour and the z axis (normal) in the interval [0, 180]
205  Eigen::Vector3f no = neighbour - origin;
206  no.normalize ();
207  float theta = normal.dot (no);
208  theta = pcl::rad2deg (std::acos (std::min (1.0f, std::max (-1.0f, theta))));
209 
210  // Compute the Bin(j, k, l) coordinates of current neighbour
211  const auto rad_min = std::lower_bound(std::next (radii_interval_.cbegin ()), radii_interval_.cend (), r);
212  const auto theta_min = std::lower_bound(std::next (theta_divisions_.cbegin ()), theta_divisions_.cend (), theta);
213  const auto phi_min = std::lower_bound(std::next (phi_divisions_.cbegin ()), phi_divisions_.cend (), phi);
214 
215  // Bin (j, k, l)
216  const auto j = std::distance(radii_interval_.cbegin (), std::prev(rad_min));
217  const auto k = std::distance(theta_divisions_.cbegin (), std::prev(theta_min));
218  const auto l = std::distance(phi_divisions_.cbegin (), std::prev(phi_min));
219 
220  // Local point density = number of points in a sphere of radius "point_density_radius_" around the current neighbour
221  std::vector<int> neighbour_indices;
222  std::vector<float> neighbour_distances;
223  int point_density = searchForNeighbors (*surface_, nn_indices[ne], point_density_radius_, neighbour_indices, neighbour_distances);
224  // point_density is NOT always bigger than 0 (on error, searchForNeighbors returns 0), so we must check for that
225  if (point_density == 0)
226  continue;
227 
228  float w = (1.0f / static_cast<float> (point_density)) *
229  volume_lut_[(l*elevation_bins_*radius_bins_) + (k*radius_bins_) + j];
230 
231  assert (w >= 0.0);
232  if (w == std::numeric_limits<float>::infinity ())
233  PCL_ERROR ("Shape Context Error INF!\n");
234  if (std::isnan(w))
235  PCL_ERROR ("Shape Context Error IND!\n");
236  /// Accumulate w into correspondent Bin(j,k,l)
237  desc[(l*elevation_bins_*radius_bins_) + (k*radius_bins_) + j] += w;
238 
239  assert (desc[(l*elevation_bins_*radius_bins_) + (k*radius_bins_) + j] >= 0);
240  } // end for each neighbour
241 
242  // 3DSC does not define a repeatable local RF, we set it to zero to signal it to the user
243  std::fill (rf, rf + 9, 0);
244  return (true);
245 }
246 
247 //////////////////////////////////////////////////////////////////////////////////////////////
248 template <typename PointInT, typename PointNT, typename PointOutT> void
250 {
251  assert (descriptor_length_ == 1980);
252 
253  output.is_dense = true;
254  // Iterate over all points and compute the descriptors
255  for (std::size_t point_index = 0; point_index < indices_->size (); point_index++)
256  {
257  //output[point_index].descriptor.resize (descriptor_length_);
258 
259  // If the point is not finite, set the descriptor to NaN and continue
260  if (!isFinite ((*input_)[(*indices_)[point_index]]))
261  {
262  std::fill (output[point_index].descriptor, output[point_index].descriptor + descriptor_length_,
263  std::numeric_limits<float>::quiet_NaN ());
264  std::fill (output[point_index].rf, output[point_index].rf + 9, 0);
265  output.is_dense = false;
266  continue;
267  }
268 
269  std::vector<float> descriptor (descriptor_length_);
270  if (!computePoint (point_index, *normals_, output[point_index].rf, descriptor))
271  output.is_dense = false;
272  std::copy (descriptor.begin (), descriptor.end (), output[point_index].descriptor);
273  }
274 }
275 
276 #define PCL_INSTANTIATE_ShapeContext3DEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::ShapeContext3DEstimation<T,NT,OutT>;
277 
pcl::ShapeContext3DEstimation::computePoint
bool computePoint(std::size_t index, const pcl::PointCloud< PointNT > &normals, float rf[9], std::vector< float > &desc)
Estimate a descriptor for a given point.
Definition: 3dsc.hpp:133
pcl::ShapeContext3DEstimation::initCompute
bool initCompute() override
Initialize computation by allocating all the intervals and the volume lookup table.
Definition: 3dsc.hpp:53
pcl::geometry::distance
float distance(const PointT &p1, const PointT &p2)
Definition: geometry.h:60
pcl::isFinite
bool isFinite(const PointT &pt)
Tests if the 3D components of a point are all finite param[in] pt point to be tested return true if f...
Definition: point_tests.h:55
pcl::ShapeContext3DEstimation::PointCloudOut
typename Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
Definition: 3dsc.h:89
geometry.h
pcl::PointCloud< PointNT >
angles.h
pcl::geometry::project
void project(const PointT &point, const PointT &plane_origin, const NormalT &plane_normal, PointT &projected)
Definition: geometry.h:81
pcl::deg2rad
float deg2rad(float alpha)
Convert an angle from degrees to radians.
Definition: angles.hpp:67
pcl::ShapeContext3DEstimation::computeFeature
void computeFeature(PointCloudOut &output) override
Estimate the actual feature.
Definition: 3dsc.hpp:249
pcl::FeatureFromNormals
Definition: feature.h:311
pcl::Vector3fMapConst
const Eigen::Map< const Eigen::Vector3f > Vector3fMapConst
Definition: point_types.hpp:181
pcl::utils::equal
bool equal(T val1, T val2, T eps=std::numeric_limits< T >::min())
Check if val1 and val2 are equal to an epsilon extent.
Definition: utils.h:55
pcl::rad2deg
float rad2deg(float alpha)
Convert an angle from radians to degrees.
Definition: angles.hpp:61