Point Cloud Library (PCL)  1.11.1-dev
iss_3d.hpp
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37 
38 #ifndef PCL_ISS_KEYPOINT3D_IMPL_H_
39 #define PCL_ISS_KEYPOINT3D_IMPL_H_
40 
41 #include <Eigen/Eigenvalues> // for SelfAdjointEigenSolver
42 #include <pcl/features/boundary.h>
43 #include <pcl/features/normal_3d.h>
44 #include <pcl/features/integral_image_normal.h>
45 
46 #include <pcl/keypoints/iss_3d.h>
47 
48 //////////////////////////////////////////////////////////////////////////////////////////////
49 template<typename PointInT, typename PointOutT, typename NormalT> void
51 {
52  salient_radius_ = salient_radius;
53 }
54 
55 //////////////////////////////////////////////////////////////////////////////////////////////
56 template<typename PointInT, typename PointOutT, typename NormalT> void
58 {
59  non_max_radius_ = non_max_radius;
60 }
61 
62 //////////////////////////////////////////////////////////////////////////////////////////////
63 template<typename PointInT, typename PointOutT, typename NormalT> void
65 {
66  normal_radius_ = normal_radius;
67 }
68 
69 //////////////////////////////////////////////////////////////////////////////////////////////
70 template<typename PointInT, typename PointOutT, typename NormalT> void
72 {
73  border_radius_ = border_radius;
74 }
75 
76 //////////////////////////////////////////////////////////////////////////////////////////////
77 template<typename PointInT, typename PointOutT, typename NormalT> void
79 {
80  gamma_21_ = gamma_21;
81 }
82 
83 //////////////////////////////////////////////////////////////////////////////////////////////
84 template<typename PointInT, typename PointOutT, typename NormalT> void
86 {
87  gamma_32_ = gamma_32;
88 }
89 
90 //////////////////////////////////////////////////////////////////////////////////////////////
91 template<typename PointInT, typename PointOutT, typename NormalT> void
93 {
94  min_neighbors_ = min_neighbors;
95 }
96 
97 //////////////////////////////////////////////////////////////////////////////////////////////
98 template<typename PointInT, typename PointOutT, typename NormalT> void
100 {
101  normals_ = normals;
102 }
103 
104 //////////////////////////////////////////////////////////////////////////////////////////////
105 template<typename PointInT, typename PointOutT, typename NormalT> bool*
106 pcl::ISSKeypoint3D<PointInT, PointOutT, NormalT>::getBoundaryPoints (PointCloudIn &input, double border_radius, float angle_threshold)
107 {
108  bool* edge_points = new bool [input.size ()];
109 
110  Eigen::Vector4f u = Eigen::Vector4f::Zero ();
111  Eigen::Vector4f v = Eigen::Vector4f::Zero ();
112 
114  boundary_estimator.setInputCloud (input_);
115 
116 #pragma omp parallel for \
117  default(none) \
118  shared(angle_threshold, boundary_estimator, border_radius, edge_points, input) \
119  firstprivate(u, v) \
120  num_threads(threads_)
121  for (int index = 0; index < int (input.size ()); index++)
122  {
123  edge_points[index] = false;
124  PointInT current_point = input[index];
125 
126  if (pcl::isFinite(current_point))
127  {
128  std::vector<int> nn_indices;
129  std::vector<float> nn_distances;
130  int n_neighbors;
131 
132  this->searchForNeighbors (static_cast<int> (index), border_radius, nn_indices, nn_distances);
133 
134  n_neighbors = static_cast<int> (nn_indices.size ());
135 
136  if (n_neighbors >= min_neighbors_)
137  {
138  boundary_estimator.getCoordinateSystemOnPlane ((*normals_)[index], u, v);
139 
140  if (boundary_estimator.isBoundaryPoint (input, static_cast<int> (index), nn_indices, u, v, angle_threshold))
141  edge_points[index] = true;
142  }
143  }
144  }
145 
146  return (edge_points);
147 }
148 
149 //////////////////////////////////////////////////////////////////////////////////////////////
150 template<typename PointInT, typename PointOutT, typename NormalT> void
151 pcl::ISSKeypoint3D<PointInT, PointOutT, NormalT>::getScatterMatrix (const int& current_index, Eigen::Matrix3d &cov_m)
152 {
153  const PointInT& current_point = (*input_)[current_index];
154 
155  double central_point[3];
156  memset(central_point, 0, sizeof(double) * 3);
157 
158  central_point[0] = current_point.x;
159  central_point[1] = current_point.y;
160  central_point[2] = current_point.z;
161 
162  cov_m = Eigen::Matrix3d::Zero ();
163 
164  std::vector<int> nn_indices;
165  std::vector<float> nn_distances;
166  int n_neighbors;
167 
168  this->searchForNeighbors (current_index, salient_radius_, nn_indices, nn_distances);
169 
170  n_neighbors = static_cast<int> (nn_indices.size ());
171 
172  if (n_neighbors < min_neighbors_)
173  return;
174 
175  double cov[9];
176  memset(cov, 0, sizeof(double) * 9);
177 
178  for (int n_idx = 0; n_idx < n_neighbors; n_idx++)
179  {
180  const PointInT& n_point = (*input_)[nn_indices[n_idx]];
181 
182  double neigh_point[3];
183  memset(neigh_point, 0, sizeof(double) * 3);
184 
185  neigh_point[0] = n_point.x;
186  neigh_point[1] = n_point.y;
187  neigh_point[2] = n_point.z;
188 
189  for (int i = 0; i < 3; i++)
190  for (int j = 0; j < 3; j++)
191  cov[i * 3 + j] += (neigh_point[i] - central_point[i]) * (neigh_point[j] - central_point[j]);
192  }
193 
194  cov_m << cov[0], cov[1], cov[2],
195  cov[3], cov[4], cov[5],
196  cov[6], cov[7], cov[8];
197 }
198 
199 //////////////////////////////////////////////////////////////////////////////////////////////
200 template<typename PointInT, typename PointOutT, typename NormalT> bool
202 {
204  {
205  PCL_ERROR ("[pcl::%s::initCompute] init failed!\n", name_.c_str ());
206  return (false);
207  }
208  if (salient_radius_ <= 0)
209  {
210  PCL_ERROR ("[pcl::%s::initCompute] : the salient radius (%f) must be strict positive!\n",
211  name_.c_str (), salient_radius_);
212  return (false);
213  }
214  if (non_max_radius_ <= 0)
215  {
216  PCL_ERROR ("[pcl::%s::initCompute] : the non maxima radius (%f) must be strict positive!\n",
217  name_.c_str (), non_max_radius_);
218  return (false);
219  }
220  if (gamma_21_ <= 0)
221  {
222  PCL_ERROR ("[pcl::%s::initCompute] : the threshold on the ratio between the 2nd and the 1rst eigenvalue (%f) must be strict positive!\n",
223  name_.c_str (), gamma_21_);
224  return (false);
225  }
226  if (gamma_32_ <= 0)
227  {
228  PCL_ERROR ("[pcl::%s::initCompute] : the threshold on the ratio between the 3rd and the 2nd eigenvalue (%f) must be strict positive!\n",
229  name_.c_str (), gamma_32_);
230  return (false);
231  }
232  if (min_neighbors_ <= 0)
233  {
234  PCL_ERROR ("[pcl::%s::initCompute] : the minimum number of neighbors (%f) must be strict positive!\n",
235  name_.c_str (), min_neighbors_);
236  return (false);
237  }
238 
239  delete[] third_eigen_value_;
240 
241  third_eigen_value_ = new double[input_->size ()];
242  memset(third_eigen_value_, 0, sizeof(double) * input_->size ());
243 
244  delete[] edge_points_;
245 
246  if (border_radius_ > 0.0)
247  {
248  if (normals_->empty ())
249  {
250  if (normal_radius_ <= 0.)
251  {
252  PCL_ERROR ("[pcl::%s::initCompute] : the radius used to estimate surface normals (%f) must be positive!\n",
253  name_.c_str (), normal_radius_);
254  return (false);
255  }
256 
257  PointCloudNPtr normal_ptr (new PointCloudN ());
258  if (input_->height == 1 )
259  {
261  normal_estimation.setInputCloud (surface_);
262  normal_estimation.setRadiusSearch (normal_radius_);
263  normal_estimation.compute (*normal_ptr);
264  }
265  else
266  {
269  normal_estimation.setInputCloud (surface_);
270  normal_estimation.setNormalSmoothingSize (5.0);
271  normal_estimation.compute (*normal_ptr);
272  }
273  normals_ = normal_ptr;
274  }
275  if (normals_->size () != surface_->size ())
276  {
277  PCL_ERROR ("[pcl::%s::initCompute] normals given, but the number of normals does not match the number of input points!\n", name_.c_str ());
278  return (false);
279  }
280  }
281  else if (border_radius_ < 0.0)
282  {
283  PCL_ERROR ("[pcl::%s::initCompute] : the border radius used to estimate boundary points (%f) must be positive!\n",
284  name_.c_str (), border_radius_);
285  return (false);
286  }
287 
288  return (true);
289 }
290 
291 //////////////////////////////////////////////////////////////////////////////////////////////
292 template<typename PointInT, typename PointOutT, typename NormalT> void
294 {
295  // Make sure the output cloud is empty
296  output.clear ();
297 
298  if (border_radius_ > 0.0)
299  edge_points_ = getBoundaryPoints (*(input_->makeShared ()), border_radius_, angle_threshold_);
300 
301  bool* borders = new bool [input_->size()];
302 
303 #pragma omp parallel for \
304  default(none) \
305  shared(borders) \
306  num_threads(threads_)
307  for (int index = 0; index < int (input_->size ()); index++)
308  {
309  borders[index] = false;
310  PointInT current_point = (*input_)[index];
311 
312  if ((border_radius_ > 0.0) && (pcl::isFinite(current_point)))
313  {
314  std::vector<int> nn_indices;
315  std::vector<float> nn_distances;
316 
317  this->searchForNeighbors (static_cast<int> (index), border_radius_, nn_indices, nn_distances);
318 
319  for (const int &nn_index : nn_indices)
320  {
321  if (edge_points_[nn_index])
322  {
323  borders[index] = true;
324  break;
325  }
326  }
327  }
328  }
329 
330 #ifdef _OPENMP
331  Eigen::Vector3d *omp_mem = new Eigen::Vector3d[threads_];
332 
333  for (std::size_t i = 0; i < threads_; i++)
334  omp_mem[i].setZero (3);
335 #else
336  Eigen::Vector3d *omp_mem = new Eigen::Vector3d[1];
337 
338  omp_mem[0].setZero (3);
339 #endif
340 
341  double *prg_local_mem = new double[input_->size () * 3];
342  double **prg_mem = new double * [input_->size ()];
343 
344  for (std::size_t i = 0; i < input_->size (); i++)
345  prg_mem[i] = prg_local_mem + 3 * i;
346 
347 #pragma omp parallel for \
348  default(none) \
349  shared(borders, omp_mem, prg_mem) \
350  num_threads(threads_)
351  for (int index = 0; index < static_cast<int> (input_->size ()); index++)
352  {
353 #ifdef _OPENMP
354  int tid = omp_get_thread_num ();
355 #else
356  int tid = 0;
357 #endif
358  PointInT current_point = (*input_)[index];
359 
360  if ((!borders[index]) && pcl::isFinite(current_point))
361  {
362  //if the considered point is not a border point and the point is "finite", then compute the scatter matrix
363  Eigen::Matrix3d cov_m = Eigen::Matrix3d::Zero ();
364  getScatterMatrix (static_cast<int> (index), cov_m);
365 
366  Eigen::SelfAdjointEigenSolver<Eigen::Matrix3d> solver (cov_m);
367 
368  const double& e1c = solver.eigenvalues ()[2];
369  const double& e2c = solver.eigenvalues ()[1];
370  const double& e3c = solver.eigenvalues ()[0];
371 
372  if (!std::isfinite (e1c) || !std::isfinite (e2c) || !std::isfinite (e3c))
373  continue;
374 
375  if (e3c < 0)
376  {
377  PCL_WARN ("[pcl::%s::detectKeypoints] : The third eigenvalue is negative! Skipping the point with index %i.\n",
378  name_.c_str (), index);
379  continue;
380  }
381 
382  omp_mem[tid][0] = e2c / e1c;
383  omp_mem[tid][1] = e3c / e2c;;
384  omp_mem[tid][2] = e3c;
385  }
386 
387  for (Eigen::Index d = 0; d < omp_mem[tid].size (); d++)
388  prg_mem[index][d] = omp_mem[tid][d];
389  }
390 
391  for (int index = 0; index < int (input_->size ()); index++)
392  {
393  if (!borders[index])
394  {
395  if ((prg_mem[index][0] < gamma_21_) && (prg_mem[index][1] < gamma_32_))
396  third_eigen_value_[index] = prg_mem[index][2];
397  }
398  }
399 
400  bool* feat_max = new bool [input_->size()];
401 
402 #pragma omp parallel for \
403  default(none) \
404  shared(feat_max) \
405  num_threads(threads_)
406  for (int index = 0; index < int (input_->size ()); index++)
407  {
408  feat_max [index] = false;
409  PointInT current_point = (*input_)[index];
410 
411  if ((third_eigen_value_[index] > 0.0) && (pcl::isFinite(current_point)))
412  {
413  std::vector<int> nn_indices;
414  std::vector<float> nn_distances;
415  int n_neighbors;
416 
417  this->searchForNeighbors (static_cast<int> (index), non_max_radius_, nn_indices, nn_distances);
418 
419  n_neighbors = static_cast<int> (nn_indices.size ());
420 
421  if (n_neighbors >= min_neighbors_)
422  {
423  bool is_max = true;
424 
425  for (int j = 0 ; j < n_neighbors; j++)
426  if (third_eigen_value_[index] < third_eigen_value_[nn_indices[j]])
427  is_max = false;
428  if (is_max)
429  feat_max[index] = true;
430  }
431  }
432  }
433 
434 #pragma omp parallel for \
435  default(none) \
436  shared(feat_max, output) \
437  num_threads(threads_)
438  for (int index = 0; index < int (input_->size ()); index++)
439  {
440  if (feat_max[index])
441 #pragma omp critical
442  {
443  PointOutT p;
444  p.getVector3fMap () = (*input_)[index].getVector3fMap ();
445  output.push_back(p);
446  keypoints_indices_->indices.push_back (index);
447  }
448  }
449 
450  output.header = input_->header;
451  output.width = output.size ();
452  output.height = 1;
453 
454  // Clear the contents of variables and arrays before the beginning of the next computation.
455  if (border_radius_ > 0.0)
456  normals_.reset (new pcl::PointCloud<NormalT>);
457 
458  delete[] borders;
459  delete[] prg_mem;
460  delete[] prg_local_mem;
461  delete[] feat_max;
462  delete[] omp_mem;
463 }
464 
465 #define PCL_INSTANTIATE_ISSKeypoint3D(T,U,N) template class PCL_EXPORTS pcl::ISSKeypoint3D<T,U,N>;
466 
467 #endif /* PCL_ISS_3D_IMPL_H_ */
pcl::NormalEstimation
NormalEstimation estimates local surface properties (surface normals and curvatures)at each 3D point.
Definition: normal_3d.h:243
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::ISSKeypoint3D::PointCloudNConstPtr
typename PointCloudN::ConstPtr PointCloudNConstPtr
Definition: iss_3d.h:96
pcl::IntegralImageNormalEstimation
Surface normal estimation on organized data using integral images.
Definition: integral_image_normal.h:66
pcl::ISSKeypoint3D::detectKeypoints
void detectKeypoints(PointCloudOut &output) override
Detect the keypoints by performing the EVD of the scatter matrix.
Definition: iss_3d.hpp:293
pcl::ISSKeypoint3D::getBoundaryPoints
bool * getBoundaryPoints(PointCloudIn &input, double border_radius, float angle_threshold)
Compute the boundary points for the given input cloud.
Definition: iss_3d.hpp:106
pcl::ISSKeypoint3D::setThreshold32
void setThreshold32(double gamma_32)
Set the upper bound on the ratio between the third and the second eigenvalue.
Definition: iss_3d.hpp:85
pcl::ISSKeypoint3D::initCompute
bool initCompute() override
Perform the initial checks before computing the keypoints.
Definition: iss_3d.hpp:201
pcl::PointCloud< NormalT >
pcl::IntegralImageNormalEstimation::setInputCloud
void setInputCloud(const typename PointCloudIn::ConstPtr &cloud) override
Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method)
Definition: integral_image_normal.h:233
pcl::IntegralImageNormalEstimation::setNormalEstimationMethod
void setNormalEstimationMethod(NormalEstimationMethod normal_estimation_method)
Set the normal estimation method.
Definition: integral_image_normal.h:215
pcl::PCLBase< PointInT >::setInputCloud
virtual void setInputCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset.
Definition: pcl_base.hpp:65
pcl::BoundaryEstimation::isBoundaryPoint
bool isBoundaryPoint(const pcl::PointCloud< PointInT > &cloud, int q_idx, const std::vector< int > &indices, const Eigen::Vector4f &u, const Eigen::Vector4f &v, const float angle_threshold)
Check whether a point is a boundary point in a planar patch of projected points given by indices.
Definition: boundary.hpp:51
pcl::BoundaryEstimation
BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle cr...
Definition: boundary.h:80
pcl::ISSKeypoint3D::getScatterMatrix
void getScatterMatrix(const int &current_index, Eigen::Matrix3d &cov_m)
Compute the scatter matrix for a point index.
Definition: iss_3d.hpp:151
pcl::NormalEstimation::setInputCloud
void setInputCloud(const PointCloudConstPtr &cloud) override
Provide a pointer to the input dataset.
Definition: normal_3d.h:332
pcl::BoundaryEstimation::getCoordinateSystemOnPlane
void getCoordinateSystemOnPlane(const PointNT &p_coeff, Eigen::Vector4f &u, Eigen::Vector4f &v)
Get a u-v-n coordinate system that lies on a plane defined by its normal.
Definition: boundary.h:160
pcl::IntegralImageNormalEstimation::setNormalSmoothingSize
void setNormalSmoothingSize(float normal_smoothing_size)
Set the normal smoothing size.
Definition: integral_image_normal.h:191
pcl::Feature::compute
void compute(PointCloudOut &output)
Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using th...
Definition: feature.hpp:194
pcl::ISSKeypoint3D::setNormals
void setNormals(const PointCloudNConstPtr &normals)
Set the normals if pre-calculated normals are available.
Definition: iss_3d.hpp:99
pcl::ISSKeypoint3D::PointCloudIn
typename Keypoint< PointInT, PointOutT >::PointCloudIn PointCloudIn
Definition: iss_3d.h:91
pcl::ISSKeypoint3D::setNormalRadius
void setNormalRadius(double normal_radius)
Set the radius used for the estimation of the surface normals of the input cloud.
Definition: iss_3d.hpp:64
pcl::ISSKeypoint3D::setThreshold21
void setThreshold21(double gamma_21)
Set the upper bound on the ratio between the second and the first eigenvalue.
Definition: iss_3d.hpp:78
pcl::ISSKeypoint3D::PointCloudOut
typename Keypoint< PointInT, PointOutT >::PointCloudOut PointCloudOut
Definition: iss_3d.h:92
pcl::Feature::setRadiusSearch
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:201
pcl::Keypoint
Keypoint represents the base class for key points.
Definition: keypoint.h:49
pcl::ISSKeypoint3D::setNonMaxRadius
void setNonMaxRadius(double non_max_radius)
Set the radius for the application of the non maxima supression algorithm.
Definition: iss_3d.hpp:57
pcl::ISSKeypoint3D::setBorderRadius
void setBorderRadius(double border_radius)
Set the radius used for the estimation of the boundary points.
Definition: iss_3d.hpp:71
pcl::ISSKeypoint3D::setSalientRadius
void setSalientRadius(double salient_radius)
Set the radius of the spherical neighborhood used to compute the scatter matrix.
Definition: iss_3d.hpp:50
pcl::ISSKeypoint3D::PointCloudNPtr
typename PointCloudN::Ptr PointCloudNPtr
Definition: iss_3d.h:95
pcl::ISSKeypoint3D::setMinNeighbors
void setMinNeighbors(int min_neighbors)
Set the minimum number of neighbors that has to be found while applying the non maxima suppression al...
Definition: iss_3d.hpp:92