Point Cloud Library (PCL)  1.9.1-dev
usc.hpp
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40 
41 #ifndef PCL_FEATURES_IMPL_USC_HPP_
42 #define PCL_FEATURES_IMPL_USC_HPP_
43 
44 #include <pcl/features/usc.h>
45 #include <pcl/features/shot_lrf.h>
46 #include <pcl/common/geometry.h>
47 #include <pcl/common/angles.h>
48 #include <pcl/common/utils.h>
49 
50 //////////////////////////////////////////////////////////////////////////////////////////////
51 template <typename PointInT, typename PointOutT, typename PointRFT> bool
53 {
55  {
56  PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
57  return (false);
58  }
59 
60  // Default LRF estimation alg: SHOTLocalReferenceFrameEstimation
62  lrf_estimator->setRadiusSearch (local_radius_);
63  lrf_estimator->setInputCloud (input_);
64  lrf_estimator->setIndices (indices_);
65  if (!fake_surface_)
66  lrf_estimator->setSearchSurface(surface_);
67 
69  {
70  PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
71  return (false);
72  }
73 
74  if (search_radius_< min_radius_)
75  {
76  PCL_ERROR ("[pcl::%s::initCompute] search_radius_ must be GREATER than min_radius_.\n", getClassName ().c_str ());
77  return (false);
78  }
79 
80  // Update descriptor length
81  descriptor_length_ = elevation_bins_ * azimuth_bins_ * radius_bins_;
82 
83  // Compute radial, elevation and azimuth divisions
84  float azimuth_interval = 360.0f / static_cast<float> (azimuth_bins_);
85  float elevation_interval = 180.0f / static_cast<float> (elevation_bins_);
86 
87  // Reallocate divisions and volume lut
88  radii_interval_.clear ();
89  phi_divisions_.clear ();
90  theta_divisions_.clear ();
91  volume_lut_.clear ();
92 
93  // Fills radii interval based on formula (1) in section 2.1 of Frome's paper
94  radii_interval_.resize (radius_bins_ + 1);
95  for (std::size_t j = 0; j < radius_bins_ + 1; j++)
96  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_))));
97 
98  // Fill theta didvisions of elevation
99  theta_divisions_.resize (elevation_bins_+1);
100  for (std::size_t k = 0; k < elevation_bins_+1; k++)
101  theta_divisions_[k] = static_cast<float> (k) * elevation_interval;
102 
103  // Fill phi didvisions of elevation
104  phi_divisions_.resize (azimuth_bins_+1);
105  for (std::size_t l = 0; l < azimuth_bins_+1; l++)
106  phi_divisions_[l] = static_cast<float> (l) * azimuth_interval;
107 
108  // LookUp Table that contains the volume of all the bins
109  // "phi" term of the volume integral
110  // "integr_phi" has always the same value so we compute it only one time
111  float integr_phi = pcl::deg2rad (phi_divisions_[1]) - pcl::deg2rad (phi_divisions_[0]);
112  // exponential to compute the cube root using pow
113  float e = 1.0f / 3.0f;
114  // Resize volume look up table
115  volume_lut_.resize (radius_bins_ * elevation_bins_ * azimuth_bins_);
116  // Fill volumes look up table
117  for (std::size_t j = 0; j < radius_bins_; j++)
118  {
119  // "r" term of the volume integral
120  float integr_r = (radii_interval_[j+1]*radii_interval_[j+1]*radii_interval_[j+1] / 3) - (radii_interval_[j]*radii_interval_[j]*radii_interval_[j]/ 3);
121 
122  for (std::size_t k = 0; k < elevation_bins_; k++)
123  {
124  // "theta" term of the volume integral
125  float integr_theta = std::cos (deg2rad (theta_divisions_[k])) - std::cos (deg2rad (theta_divisions_[k+1]));
126  // Volume
127  float V = integr_phi * integr_theta * integr_r;
128  // Compute cube root of the computed volume commented for performance but left
129  // here for clarity
130  // float cbrt = pow(V, e);
131  // cbrt = 1 / cbrt;
132 
133  for (std::size_t l = 0; l < azimuth_bins_; l++)
134  // Store in lut 1/cbrt
135  //volume_lut_[ (l*elevation_bins_*radius_bins_) + k*radius_bins_ + j ] = cbrt;
136  volume_lut_[(l*elevation_bins_*radius_bins_) + k*radius_bins_ + j] = 1.0f / powf (V, e);
137  }
138  }
139  return (true);
140 }
141 
142 //////////////////////////////////////////////////////////////////////////////////////////////
143 template <typename PointInT, typename PointOutT, typename PointRFT> void
144 pcl::UniqueShapeContext<PointInT, PointOutT, PointRFT>::computePointDescriptor (std::size_t index, /*float rf[9],*/ std::vector<float> &desc)
145 {
146  pcl::Vector3fMapConst origin = input_->points[(*indices_)[index]].getVector3fMap ();
147 
148  const Eigen::Vector3f x_axis (frames_->points[index].x_axis[0],
149  frames_->points[index].x_axis[1],
150  frames_->points[index].x_axis[2]);
151  //const Eigen::Vector3f& y_axis = frames_->points[index].y_axis.getNormalVector3fMap ();
152  const Eigen::Vector3f normal (frames_->points[index].z_axis[0],
153  frames_->points[index].z_axis[1],
154  frames_->points[index].z_axis[2]);
155 
156  // Find every point within specified search_radius_
157  std::vector<int> nn_indices;
158  std::vector<float> nn_dists;
159  const std::size_t neighb_cnt = searchForNeighbors ((*indices_)[index], search_radius_, nn_indices, nn_dists);
160  // For each point within radius
161  for (std::size_t ne = 0; ne < neighb_cnt; ne++)
162  {
163  if (pcl::utils::equal(nn_dists[ne], 0.0f))
164  continue;
165  // Get neighbours coordinates
166  Eigen::Vector3f neighbour = surface_->points[nn_indices[ne]].getVector3fMap ();
167 
168  // ----- Compute current neighbour polar coordinates -----
169 
170  // Get distance between the neighbour and the origin
171  float r = std::sqrt (nn_dists[ne]);
172 
173  // Project point into the tangent plane
174  Eigen::Vector3f proj;
175  pcl::geometry::project (neighbour, origin, normal, proj);
176  proj -= origin;
177 
178  // Normalize to compute the dot product
179  proj.normalize ();
180 
181  // Compute the angle between the projection and the x axis in the interval [0,360]
182  Eigen::Vector3f cross = x_axis.cross (proj);
183  float phi = rad2deg (std::atan2 (cross.norm (), x_axis.dot (proj)));
184  phi = cross.dot (normal) < 0.f ? (360.0f - phi) : phi;
185  /// Compute the angle between the neighbour and the z axis (normal) in the interval [0, 180]
186  Eigen::Vector3f no = neighbour - origin;
187  no.normalize ();
188  float theta = normal.dot (no);
189  theta = pcl::rad2deg (std::acos (std::min (1.0f, std::max (-1.0f, theta))));
190 
191  /// Bin (j, k, l)
192  std::size_t j = 0;
193  std::size_t k = 0;
194  std::size_t l = 0;
195 
196  /// Compute the Bin(j, k, l) coordinates of current neighbour
197  for (std::size_t rad = 1; rad < radius_bins_ + 1; rad++)
198  {
199  if (r <= radii_interval_[rad])
200  {
201  j = rad - 1;
202  break;
203  }
204  }
205 
206  for (std::size_t ang = 1; ang < elevation_bins_ + 1; ang++)
207  {
208  if (theta <= theta_divisions_[ang])
209  {
210  k = ang - 1;
211  break;
212  }
213  }
214 
215  for (std::size_t ang = 1; ang < azimuth_bins_ + 1; ang++)
216  {
217  if (phi <= phi_divisions_[ang])
218  {
219  l = ang - 1;
220  break;
221  }
222  }
223 
224  /// Local point density = number of points in a sphere of radius "point_density_radius_" around the current neighbour
225  std::vector<int> neighbour_indices;
226  std::vector<float> neighbour_didtances;
227  float point_density = static_cast<float> (searchForNeighbors (*surface_, nn_indices[ne], point_density_radius_, neighbour_indices, neighbour_didtances));
228  /// point_density is always bigger than 0 because FindPointsWithinRadius returns at least the point itself
229  float w = (1.0f / point_density) * volume_lut_[(l*elevation_bins_*radius_bins_) +
230  (k*radius_bins_) +
231  j];
232 
233  assert (w >= 0.0);
234  if (w == std::numeric_limits<float>::infinity ())
235  PCL_ERROR ("Shape Context Error INF!\n");
236  if (std::isnan(w))
237  PCL_ERROR ("Shape Context Error IND!\n");
238  /// Accumulate w into correspondent Bin(j,k,l)
239  desc[(l*elevation_bins_*radius_bins_) + (k*radius_bins_) + j] += w;
240 
241  assert (desc[(l*elevation_bins_*radius_bins_) + (k*radius_bins_) + j] >= 0);
242  } // end for each neighbour
243 }
244 
245 //////////////////////////////////////////////////////////////////////////////////////////////
246 template <typename PointInT, typename PointOutT, typename PointRFT> void
248 {
249  assert (descriptor_length_ == 1960);
250 
251  output.is_dense = true;
252 
253  for (std::size_t point_index = 0; point_index < indices_->size (); ++point_index)
254  {
255  //output[point_index].descriptor.resize (descriptor_length_);
256 
257  // If the point is not finite, set the descriptor to NaN and continue
258  const PointRFT& current_frame = (*frames_)[point_index];
259  if (!isFinite ((*input_)[(*indices_)[point_index]]) ||
260  !std::isfinite (current_frame.x_axis[0]) ||
261  !std::isfinite (current_frame.y_axis[0]) ||
262  !std::isfinite (current_frame.z_axis[0]) )
263  {
264  for (std::size_t i = 0; i < descriptor_length_; ++i)
265  output[point_index].descriptor[i] = std::numeric_limits<float>::quiet_NaN ();
266 
267  memset (output[point_index].rf, 0, sizeof (output[point_index].rf[0]) * 9);
268  output.is_dense = false;
269  continue;
270  }
271 
272  for (int d = 0; d < 3; ++d)
273  {
274  output.points[point_index].rf[0 + d] = current_frame.x_axis[d];
275  output.points[point_index].rf[3 + d] = current_frame.y_axis[d];
276  output.points[point_index].rf[6 + d] = current_frame.z_axis[d];
277  }
278 
279  std::vector<float> descriptor (descriptor_length_);
280  computePointDescriptor (point_index, descriptor);
281  for (std::size_t j = 0; j < descriptor_length_; ++j)
282  output [point_index].descriptor[j] = descriptor[j];
283  }
284 }
285 
286 #define PCL_INSTANTIATE_UniqueShapeContext(T,OutT,RFT) template class PCL_EXPORTS pcl::UniqueShapeContext<T,OutT,RFT>;
287 
288 #endif
void setSearchSurface(const PointCloudInConstPtr &cloud)
Provide a pointer to a dataset to add additional information to estimate the features for every point...
Definition: feature.h:148
void project(const PointT &point, const PointT &plane_origin, const NormalT &plane_normal, PointT &projected)
Definition: geometry.h:81
bool initCompute() override
Initialize computation by allocating all the intervals and the volume lookup table.
Definition: usc.hpp:52
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
float deg2rad(float alpha)
Convert an angle from degrees to radians.
Definition: angles.hpp:67
std::vector< PointT, Eigen::aligned_allocator< PointT > > points
The point data.
Definition: point_cloud.h:394
void computeFeature(PointCloudOut &output) override
The actual feature computation.
Definition: usc.hpp:247
Defines some geometrical functions and utility functions.
float rad2deg(float alpha)
Convert an angle from radians to degrees.
Definition: angles.hpp:61
void setRadiusSearch(double radius)
Set the sphere radius that is to be used for determining the nearest neighbors used for the feature e...
Definition: feature.h:200
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:54
const Eigen::Map< const Eigen::Vector3f > Vector3fMapConst
virtual void setIndices(const IndicesPtr &indices)
Provide a pointer to the vector of indices that represents the input data.
Definition: pcl_base.hpp:72
void computePointDescriptor(std::size_t index, std::vector< float > &desc)
Compute 3D shape context feature descriptor.
Definition: usc.hpp:144
SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the ...
Definition: shot_lrf.h:65
virtual void setInputCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset.
Definition: pcl_base.hpp:65
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields)...
Definition: point_cloud.h:402
Feature represents the base feature class.
Definition: feature.h:105
FeatureWithLocalReferenceFrames provides a public interface for descriptor extractor classes which ne...
Definition: feature.h:447
Define standard C methods to do angle calculations.
boost::shared_ptr< SHOTLocalReferenceFrameEstimation< PointInT, PointOutT > > Ptr
Definition: shot_lrf.h:68