Point Cloud Library (PCL) 1.13.0
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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//////////////////////////////////////////////////////////////////////////////////////////////
49template<typename PointInT, typename PointOutT, typename NormalT> void
51{
52 salient_radius_ = salient_radius;
53}
54
55//////////////////////////////////////////////////////////////////////////////////////////////
56template<typename PointInT, typename PointOutT, typename NormalT> void
58{
59 non_max_radius_ = non_max_radius;
60}
61
62//////////////////////////////////////////////////////////////////////////////////////////////
63template<typename PointInT, typename PointOutT, typename NormalT> void
65{
66 normal_radius_ = normal_radius;
67}
68
69//////////////////////////////////////////////////////////////////////////////////////////////
70template<typename PointInT, typename PointOutT, typename NormalT> void
72{
73 border_radius_ = border_radius;
74}
75
76//////////////////////////////////////////////////////////////////////////////////////////////
77template<typename PointInT, typename PointOutT, typename NormalT> void
79{
80 gamma_21_ = gamma_21;
81}
82
83//////////////////////////////////////////////////////////////////////////////////////////////
84template<typename PointInT, typename PointOutT, typename NormalT> void
86{
87 gamma_32_ = gamma_32;
88}
89
90//////////////////////////////////////////////////////////////////////////////////////////////
91template<typename PointInT, typename PointOutT, typename NormalT> void
93{
94 min_neighbors_ = min_neighbors;
95}
96
97//////////////////////////////////////////////////////////////////////////////////////////////
98template<typename PointInT, typename PointOutT, typename NormalT> void
103
104//////////////////////////////////////////////////////////////////////////////////////////////
105template<typename PointInT, typename PointOutT, typename NormalT> void
107{
108 if (nr_threads == 0)
109#ifdef _OPENMP
110 threads_ = omp_get_num_procs();
111#else
112 threads_ = 1;
113#endif
114 else
115 threads_ = nr_threads;
116}
117
118//////////////////////////////////////////////////////////////////////////////////////////////
119template<typename PointInT, typename PointOutT, typename NormalT> bool*
121{
122 bool* edge_points = new bool [input.size ()];
123
124 Eigen::Vector4f u = Eigen::Vector4f::Zero ();
125 Eigen::Vector4f v = Eigen::Vector4f::Zero ();
126
128 boundary_estimator.setInputCloud (input_);
129
130#pragma omp parallel for \
131 default(none) \
132 shared(angle_threshold, boundary_estimator, border_radius, edge_points, input) \
133 firstprivate(u, v) \
134 num_threads(threads_)
135 for (int index = 0; index < int (input.size ()); index++)
136 {
137 edge_points[index] = false;
138 PointInT current_point = input[index];
139
140 if (pcl::isFinite(current_point))
141 {
142 pcl::Indices nn_indices;
143 std::vector<float> nn_distances;
144 int n_neighbors;
145
146 this->searchForNeighbors (index, border_radius, nn_indices, nn_distances);
147
148 n_neighbors = static_cast<int> (nn_indices.size ());
149
150 if (n_neighbors >= min_neighbors_)
151 {
152 boundary_estimator.getCoordinateSystemOnPlane ((*normals_)[index], u, v);
153
154 if (boundary_estimator.isBoundaryPoint (input, static_cast<int> (index), nn_indices, u, v, angle_threshold))
155 edge_points[index] = true;
156 }
157 }
158 }
159
160 return (edge_points);
161}
162
163//////////////////////////////////////////////////////////////////////////////////////////////
164template<typename PointInT, typename PointOutT, typename NormalT> void
165pcl::ISSKeypoint3D<PointInT, PointOutT, NormalT>::getScatterMatrix (const int& current_index, Eigen::Matrix3d &cov_m)
166{
167 const PointInT& current_point = (*input_)[current_index];
168
169 double central_point[3]{};
170
171 central_point[0] = current_point.x;
172 central_point[1] = current_point.y;
173 central_point[2] = current_point.z;
174
175 cov_m = Eigen::Matrix3d::Zero ();
176
177 pcl::Indices nn_indices;
178 std::vector<float> nn_distances;
179 int n_neighbors;
180
181 this->searchForNeighbors (current_index, salient_radius_, nn_indices, nn_distances);
182
183 n_neighbors = static_cast<int> (nn_indices.size ());
184
185 if (n_neighbors < min_neighbors_)
186 return;
187
188 double cov[9]{};
189
190 for (const auto& n_idx : nn_indices)
191 {
192 const PointInT& n_point = (*input_)[n_idx];
193
194 double neigh_point[3]{};
195
196 neigh_point[0] = n_point.x;
197 neigh_point[1] = n_point.y;
198 neigh_point[2] = n_point.z;
199
200 for (int i = 0; i < 3; i++)
201 for (int j = 0; j < 3; j++)
202 cov[i * 3 + j] += (neigh_point[i] - central_point[i]) * (neigh_point[j] - central_point[j]);
203 }
204
205 cov_m << cov[0], cov[1], cov[2],
206 cov[3], cov[4], cov[5],
207 cov[6], cov[7], cov[8];
208}
209
210//////////////////////////////////////////////////////////////////////////////////////////////
211template<typename PointInT, typename PointOutT, typename NormalT> bool
213{
215 {
216 PCL_ERROR ("[pcl::%s::initCompute] init failed!\n", name_.c_str ());
217 return (false);
218 }
219 if (salient_radius_ <= 0)
220 {
221 PCL_ERROR ("[pcl::%s::initCompute] : the salient radius (%f) must be strict positive!\n",
222 name_.c_str (), salient_radius_);
223 return (false);
224 }
225 if (non_max_radius_ <= 0)
226 {
227 PCL_ERROR ("[pcl::%s::initCompute] : the non maxima radius (%f) must be strict positive!\n",
228 name_.c_str (), non_max_radius_);
229 return (false);
230 }
231 if (gamma_21_ <= 0)
232 {
233 PCL_ERROR ("[pcl::%s::initCompute] : the threshold on the ratio between the 2nd and the 1rst eigenvalue (%f) must be strict positive!\n",
234 name_.c_str (), gamma_21_);
235 return (false);
236 }
237 if (gamma_32_ <= 0)
238 {
239 PCL_ERROR ("[pcl::%s::initCompute] : the threshold on the ratio between the 3rd and the 2nd eigenvalue (%f) must be strict positive!\n",
240 name_.c_str (), gamma_32_);
241 return (false);
242 }
243 if (min_neighbors_ <= 0)
244 {
245 PCL_ERROR ("[pcl::%s::initCompute] : the minimum number of neighbors (%f) must be strict positive!\n",
246 name_.c_str (), min_neighbors_);
247 return (false);
248 }
249
250 delete[] third_eigen_value_;
251
252 third_eigen_value_ = new double[input_->size ()]{};
253
254 delete[] edge_points_;
255
256 if (border_radius_ > 0.0)
257 {
258 if (normals_->empty ())
259 {
260 if (normal_radius_ <= 0.)
261 {
262 PCL_ERROR ("[pcl::%s::initCompute] : the radius used to estimate surface normals (%f) must be positive!\n",
263 name_.c_str (), normal_radius_);
264 return (false);
265 }
266
267 PointCloudNPtr normal_ptr (new PointCloudN ());
268 if (input_->height == 1 )
269 {
271 normal_estimation.setInputCloud (surface_);
272 normal_estimation.setRadiusSearch (normal_radius_);
273 normal_estimation.compute (*normal_ptr);
274 }
275 else
276 {
279 normal_estimation.setInputCloud (surface_);
280 normal_estimation.setNormalSmoothingSize (5.0);
281 normal_estimation.compute (*normal_ptr);
282 }
283 normals_ = normal_ptr;
284 }
285 if (normals_->size () != surface_->size ())
286 {
287 PCL_ERROR ("[pcl::%s::initCompute] normals given, but the number of normals does not match the number of input points!\n", name_.c_str ());
288 return (false);
289 }
290 }
291 else if (border_radius_ < 0.0)
292 {
293 PCL_ERROR ("[pcl::%s::initCompute] : the border radius used to estimate boundary points (%f) must be positive!\n",
294 name_.c_str (), border_radius_);
295 return (false);
296 }
297
298 return (true);
299}
300
301//////////////////////////////////////////////////////////////////////////////////////////////
302template<typename PointInT, typename PointOutT, typename NormalT> void
304{
305 // Make sure the output cloud is empty
306 output.clear ();
307
308 if (border_radius_ > 0.0)
309 edge_points_ = getBoundaryPoints (*(input_->makeShared ()), border_radius_, angle_threshold_);
310
311 bool* borders = new bool [input_->size()];
312
313#pragma omp parallel for \
314 default(none) \
315 shared(borders) \
316 num_threads(threads_)
317 for (int index = 0; index < int (input_->size ()); index++)
318 {
319 borders[index] = false;
320 PointInT current_point = (*input_)[index];
321
322 if ((border_radius_ > 0.0) && (pcl::isFinite(current_point)))
323 {
324 pcl::Indices nn_indices;
325 std::vector<float> nn_distances;
326
327 this->searchForNeighbors (index, border_radius_, nn_indices, nn_distances);
328
329 for (const auto &nn_index : nn_indices)
330 {
331 if (edge_points_[nn_index])
332 {
333 borders[index] = true;
334 break;
335 }
336 }
337 }
338 }
339
340#ifdef _OPENMP
341 Eigen::Vector3d *omp_mem = new Eigen::Vector3d[threads_];
342
343 for (std::size_t i = 0; i < threads_; i++)
344 omp_mem[i].setZero (3);
345#else
346 auto *omp_mem = new Eigen::Vector3d[1];
347
348 omp_mem[0].setZero (3);
349#endif
350
351 double *prg_local_mem = new double[input_->size () * 3];
352 double **prg_mem = new double * [input_->size ()];
353
354 for (std::size_t i = 0; i < input_->size (); i++)
355 prg_mem[i] = prg_local_mem + 3 * i;
356
357#pragma omp parallel for \
358 default(none) \
359 shared(borders, omp_mem, prg_mem) \
360 num_threads(threads_)
361 for (int index = 0; index < static_cast<int> (input_->size ()); index++)
362 {
363#ifdef _OPENMP
364 int tid = omp_get_thread_num ();
365#else
366 int tid = 0;
367#endif
368 PointInT current_point = (*input_)[index];
369
370 if ((!borders[index]) && pcl::isFinite(current_point))
371 {
372 //if the considered point is not a border point and the point is "finite", then compute the scatter matrix
373 Eigen::Matrix3d cov_m = Eigen::Matrix3d::Zero ();
374 getScatterMatrix (static_cast<int> (index), cov_m);
375
376 Eigen::SelfAdjointEigenSolver<Eigen::Matrix3d> solver (cov_m);
377
378 const double& e1c = solver.eigenvalues ()[2];
379 const double& e2c = solver.eigenvalues ()[1];
380 const double& e3c = solver.eigenvalues ()[0];
381
382 if (!std::isfinite (e1c) || !std::isfinite (e2c) || !std::isfinite (e3c))
383 continue;
384
385 if (e3c < 0)
386 {
387 PCL_WARN ("[pcl::%s::detectKeypoints] : The third eigenvalue is negative! Skipping the point with index %i.\n",
388 name_.c_str (), index);
389 continue;
390 }
391
392 omp_mem[tid][0] = e2c / e1c;
393 omp_mem[tid][1] = e3c / e2c;
394 omp_mem[tid][2] = e3c;
395 }
396
397 for (Eigen::Index d = 0; d < omp_mem[tid].size (); d++)
398 prg_mem[index][d] = omp_mem[tid][d];
399 }
400
401 for (int index = 0; index < int (input_->size ()); index++)
402 {
403 if (!borders[index])
404 {
405 if ((prg_mem[index][0] < gamma_21_) && (prg_mem[index][1] < gamma_32_))
406 third_eigen_value_[index] = prg_mem[index][2];
407 }
408 }
409
410 bool* feat_max = new bool [input_->size()];
411
412#pragma omp parallel for \
413 default(none) \
414 shared(feat_max) \
415 num_threads(threads_)
416 for (int index = 0; index < int (input_->size ()); index++)
417 {
418 feat_max [index] = false;
419 PointInT current_point = (*input_)[index];
420
421 if ((third_eigen_value_[index] > 0.0) && (pcl::isFinite(current_point)))
422 {
423 pcl::Indices nn_indices;
424 std::vector<float> nn_distances;
425 int n_neighbors;
426
427 this->searchForNeighbors (index, non_max_radius_, nn_indices, nn_distances);
428
429 n_neighbors = static_cast<int> (nn_indices.size ());
430
431 if (n_neighbors >= min_neighbors_)
432 {
433 bool is_max = true;
434
435 for (const auto& j : nn_indices)
436 if (third_eigen_value_[index] < third_eigen_value_[j])
437 is_max = false;
438 if (is_max)
439 feat_max[index] = true;
440 }
441 }
442 }
443
444#pragma omp parallel for \
445 default(none) \
446 shared(feat_max, output) \
447 num_threads(threads_)
448 for (int index = 0; index < int (input_->size ()); index++)
449 {
450 if (feat_max[index])
451#pragma omp critical
452 {
453 PointOutT p;
454 p.getVector3fMap () = (*input_)[index].getVector3fMap ();
455 output.push_back(p);
456 keypoints_indices_->indices.push_back (index);
457 }
458 }
459
460 output.header = input_->header;
461 output.width = output.size ();
462 output.height = 1;
463
464 // Clear the contents of variables and arrays before the beginning of the next computation.
465 if (border_radius_ > 0.0)
466 normals_.reset (new pcl::PointCloud<NormalT>);
467
468 delete[] borders;
469 delete[] prg_mem;
470 delete[] prg_local_mem;
471 delete[] feat_max;
472 delete[] omp_mem;
473}
474
475#define PCL_INSTANTIATE_ISSKeypoint3D(T,U,N) template class PCL_EXPORTS pcl::ISSKeypoint3D<T,U,N>;
476
477#endif /* PCL_ISS_3D_IMPL_H_ */
BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle cr...
Definition boundary.h:80
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:159
bool isBoundaryPoint(const pcl::PointCloud< PointInT > &cloud, int q_idx, const pcl::Indices &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
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:198
void compute(PointCloudOut &output)
Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using th...
Definition feature.hpp:194
typename PointCloudN::ConstPtr PointCloudNConstPtr
Definition iss_3d.h:96
void setNumberOfThreads(unsigned int nr_threads=0)
Initialize the scheduler and set the number of threads to use.
Definition iss_3d.hpp:106
typename Keypoint< PointInT, PointOutT >::PointCloudIn PointCloudIn
Definition iss_3d.h:91
void setNormals(const PointCloudNConstPtr &normals)
Set the normals if pre-calculated normals are available.
Definition iss_3d.hpp:99
void setBorderRadius(double border_radius)
Set the radius used for the estimation of the boundary points.
Definition iss_3d.hpp:71
void setSalientRadius(double salient_radius)
Set the radius of the spherical neighborhood used to compute the scatter matrix.
Definition iss_3d.hpp:50
void getScatterMatrix(const int &current_index, Eigen::Matrix3d &cov_m)
Compute the scatter matrix for a point index.
Definition iss_3d.hpp:165
void setThreshold21(double gamma_21)
Set the upper bound on the ratio between the second and the first eigenvalue.
Definition iss_3d.hpp:78
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
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
void setThreshold32(double gamma_32)
Set the upper bound on the ratio between the third and the second eigenvalue.
Definition iss_3d.hpp:85
bool initCompute() override
Perform the initial checks before computing the keypoints.
Definition iss_3d.hpp:212
typename PointCloudN::Ptr PointCloudNPtr
Definition iss_3d.h:95
void setNonMaxRadius(double non_max_radius)
Set the radius for the application of the non maxima supression algorithm.
Definition iss_3d.hpp:57
bool * getBoundaryPoints(PointCloudIn &input, double border_radius, float angle_threshold)
Compute the boundary points for the given input cloud.
Definition iss_3d.hpp:120
void detectKeypoints(PointCloudOut &output) override
Detect the keypoints by performing the EVD of the scatter matrix.
Definition iss_3d.hpp:303
typename Keypoint< PointInT, PointOutT >::PointCloudOut PointCloudOut
Definition iss_3d.h:92
Surface normal estimation on organized data using integral images.
void setNormalEstimationMethod(NormalEstimationMethod normal_estimation_method)
Set the normal estimation method.
void setInputCloud(const typename PointCloudIn::ConstPtr &cloud) override
Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method)
void setNormalSmoothingSize(float normal_smoothing_size)
Set the normal smoothing size.
Keypoint represents the base class for key points.
Definition keypoint.h:49
NormalEstimation estimates local surface properties (surface normals and curvatures)at each 3D point.
Definition normal_3d.h:244
void setInputCloud(const PointCloudConstPtr &cloud) override
Provide a pointer to the input dataset.
Definition normal_3d.h:332
virtual void setInputCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset.
Definition pcl_base.hpp:65
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
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133