Point Cloud Library (PCL)  1.11.1-dev
sac_model_plane.hpp
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40 
41 #ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_PLANE_H_
42 #define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_PLANE_H_
43 
44 #include <pcl/sample_consensus/sac_model_plane.h>
45 #include <pcl/common/centroid.h>
46 #include <pcl/common/eigen.h>
47 #include <pcl/common/concatenate.h>
48 
49 //////////////////////////////////////////////////////////////////////////
50 template <typename PointT> bool
52 {
53  if (samples.size () != sample_size_)
54  {
55  PCL_ERROR ("[pcl::SampleConsensusModelPlane::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
56  return (false);
57  }
58  // Get the values at the two points
59  pcl::Array4fMapConst p0 = (*input_)[samples[0]].getArray4fMap ();
60  pcl::Array4fMapConst p1 = (*input_)[samples[1]].getArray4fMap ();
61  pcl::Array4fMapConst p2 = (*input_)[samples[2]].getArray4fMap ();
62 
63  Eigen::Array4f dy1dy2 = (p1-p0) / (p2-p0);
64 
65  return ( (dy1dy2[0] != dy1dy2[1]) || (dy1dy2[2] != dy1dy2[1]) );
66 }
67 
68 //////////////////////////////////////////////////////////////////////////
69 template <typename PointT> bool
71  const Indices &samples, Eigen::VectorXf &model_coefficients) const
72 {
73  // Need 3 samples
74  if (samples.size () != sample_size_)
75  {
76  PCL_ERROR ("[pcl::SampleConsensusModelPlane::computeModelCoefficients] Invalid set of samples given (%lu)!\n", samples.size ());
77  return (false);
78  }
79 
80  pcl::Array4fMapConst p0 = (*input_)[samples[0]].getArray4fMap ();
81  pcl::Array4fMapConst p1 = (*input_)[samples[1]].getArray4fMap ();
82  pcl::Array4fMapConst p2 = (*input_)[samples[2]].getArray4fMap ();
83 
84  // Compute the segment values (in 3d) between p1 and p0
85  Eigen::Array4f p1p0 = p1 - p0;
86  // Compute the segment values (in 3d) between p2 and p0
87  Eigen::Array4f p2p0 = p2 - p0;
88 
89  // Avoid some crashes by checking for collinearity here
90  Eigen::Array4f dy1dy2 = p1p0 / p2p0;
91  if ( (dy1dy2[0] == dy1dy2[1]) && (dy1dy2[2] == dy1dy2[1]) ) // Check for collinearity
92  {
93  return (false);
94  }
95 
96  // Compute the plane coefficients from the 3 given points in a straightforward manner
97  // calculate the plane normal n = (p2-p1) x (p3-p1) = cross (p2-p1, p3-p1)
98  model_coefficients.resize (model_size_);
99  model_coefficients[0] = p1p0[1] * p2p0[2] - p1p0[2] * p2p0[1];
100  model_coefficients[1] = p1p0[2] * p2p0[0] - p1p0[0] * p2p0[2];
101  model_coefficients[2] = p1p0[0] * p2p0[1] - p1p0[1] * p2p0[0];
102  model_coefficients[3] = 0.0f;
103 
104  // Normalize
105  model_coefficients.normalize ();
106 
107  // ... + d = 0
108  model_coefficients[3] = -1.0f * (model_coefficients.template head<4>().dot (p0.matrix ()));
109 
110  return (true);
111 }
112 
113 #define AT(POS) ((*input_)[(*indices_)[(POS)]])
114 
115 #ifdef __AVX__
116 // This function computes the distances of 8 points to the plane
117 template <typename PointT> inline __m256 pcl::SampleConsensusModelPlane<PointT>::dist8 (const std::size_t i, const __m256 &a_vec, const __m256 &b_vec, const __m256 &c_vec, const __m256 &d_vec, const __m256 &abs_help) const
118 {
119  // The andnot-function realizes an abs-operation: the sign bit is removed
120  return _mm256_andnot_ps (abs_help,
121  _mm256_add_ps (_mm256_add_ps (_mm256_mul_ps (a_vec, _mm256_set_ps (AT(i ).x, AT(i+1).x, AT(i+2).x, AT(i+3).x, AT(i+4).x, AT(i+5).x, AT(i+6).x, AT(i+7).x)),
122  _mm256_mul_ps (b_vec, _mm256_set_ps (AT(i ).y, AT(i+1).y, AT(i+2).y, AT(i+3).y, AT(i+4).y, AT(i+5).y, AT(i+6).y, AT(i+7).y))),
123  _mm256_add_ps (_mm256_mul_ps (c_vec, _mm256_set_ps (AT(i ).z, AT(i+1).z, AT(i+2).z, AT(i+3).z, AT(i+4).z, AT(i+5).z, AT(i+6).z, AT(i+7).z)),
124  d_vec))); // TODO this could be replaced by three fmadd-instructions (if available), but the speed gain would probably be minimal
125 }
126 #endif // ifdef __AVX__
127 
128 #ifdef __SSE__
129 // This function computes the distances of 4 points to the plane
130 template <typename PointT> inline __m128 pcl::SampleConsensusModelPlane<PointT>::dist4 (const std::size_t i, const __m128 &a_vec, const __m128 &b_vec, const __m128 &c_vec, const __m128 &d_vec, const __m128 &abs_help) const
131 {
132  // The andnot-function realizes an abs-operation: the sign bit is removed
133  return _mm_andnot_ps (abs_help,
134  _mm_add_ps (_mm_add_ps (_mm_mul_ps (a_vec, _mm_set_ps (AT(i ).x, AT(i+1).x, AT(i+2).x, AT(i+3).x)),
135  _mm_mul_ps (b_vec, _mm_set_ps (AT(i ).y, AT(i+1).y, AT(i+2).y, AT(i+3).y))),
136  _mm_add_ps (_mm_mul_ps (c_vec, _mm_set_ps (AT(i ).z, AT(i+1).z, AT(i+2).z, AT(i+3).z)),
137  d_vec))); // TODO this could be replaced by three fmadd-instructions (if available), but the speed gain would probably be minimal
138 }
139 #endif // ifdef __SSE__
140 
141 #undef AT
142 
143 //////////////////////////////////////////////////////////////////////////
144 template <typename PointT> void
146  const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
147 {
148  // Needs a valid set of model coefficients
149  if (!isModelValid (model_coefficients))
150  {
151  PCL_ERROR ("[pcl::SampleConsensusModelPlane::getDistancesToModel] Given model is invalid!\n");
152  return;
153  }
154 
155  distances.resize (indices_->size ());
156 
157  // Iterate through the 3d points and calculate the distances from them to the plane
158  for (std::size_t i = 0; i < indices_->size (); ++i)
159  {
160  // Calculate the distance from the point to the plane normal as the dot product
161  // D = (P-A).N/|N|
162  /*distances[i] = std::abs (model_coefficients[0] * (*input_)[(*indices_)[i]].x +
163  model_coefficients[1] * (*input_)[(*indices_)[i]].y +
164  model_coefficients[2] * (*input_)[(*indices_)[i]].z +
165  model_coefficients[3]);*/
166  Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x,
167  (*input_)[(*indices_)[i]].y,
168  (*input_)[(*indices_)[i]].z,
169  1.0f);
170  distances[i] = std::abs (model_coefficients.dot (pt));
171  }
172 }
173 
174 //////////////////////////////////////////////////////////////////////////
175 template <typename PointT> void
177  const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
178 {
179  // Needs a valid set of model coefficients
180  if (!isModelValid (model_coefficients))
181  {
182  PCL_ERROR ("[pcl::SampleConsensusModelPlane::selectWithinDistance] Given model is invalid!\n");
183  return;
184  }
185 
186  inliers.clear ();
187  error_sqr_dists_.clear ();
188  inliers.reserve (indices_->size ());
189  error_sqr_dists_.reserve (indices_->size ());
190 
191  // Iterate through the 3d points and calculate the distances from them to the plane
192  for (std::size_t i = 0; i < indices_->size (); ++i)
193  {
194  // Calculate the distance from the point to the plane normal as the dot product
195  // D = (P-A).N/|N|
196  Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x,
197  (*input_)[(*indices_)[i]].y,
198  (*input_)[(*indices_)[i]].z,
199  1.0f);
200 
201  float distance = std::abs (model_coefficients.dot (pt));
202 
203  if (distance < threshold)
204  {
205  // Returns the indices of the points whose distances are smaller than the threshold
206  inliers.push_back ((*indices_)[i]);
207  error_sqr_dists_.push_back (static_cast<double> (distance));
208  }
209  }
210 }
211 
212 //////////////////////////////////////////////////////////////////////////
213 template <typename PointT> std::size_t
215  const Eigen::VectorXf &model_coefficients, const double threshold) const
216 {
217  // Needs a valid set of model coefficients
218  if (!isModelValid (model_coefficients))
219  {
220  PCL_ERROR ("[pcl::SampleConsensusModelPlane::countWithinDistance] Given model is invalid!\n");
221  return (0);
222  }
223 #if defined (__AVX__) && defined (__AVX2__)
224  return countWithinDistanceAVX (model_coefficients, threshold);
225 #elif defined (__SSE__) && defined (__SSE2__) && defined (__SSE4_1__)
226  return countWithinDistanceSSE (model_coefficients, threshold);
227 #else
228  return countWithinDistanceStandard (model_coefficients, threshold);
229 #endif
230 }
231 
232 //////////////////////////////////////////////////////////////////////////
233 template <typename PointT> std::size_t
235  const Eigen::VectorXf &model_coefficients, const double threshold, std::size_t i) const
236 {
237  std::size_t nr_p = 0;
238  // Iterate through the 3d points and calculate the distances from them to the plane
239  for (; i < indices_->size (); ++i)
240  {
241  // Calculate the distance from the point to the plane normal as the dot product
242  // D = (P-A).N/|N|
243  Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x,
244  (*input_)[(*indices_)[i]].y,
245  (*input_)[(*indices_)[i]].z,
246  1.0f);
247  if (std::abs (model_coefficients.dot (pt)) < threshold)
248  {
249  nr_p++;
250  }
251  }
252  return (nr_p);
253 }
254 
255 //////////////////////////////////////////////////////////////////////////
256 #if defined (__SSE__) && defined (__SSE2__) && defined (__SSE4_1__)
257 template <typename PointT> std::size_t
259  const Eigen::VectorXf &model_coefficients, const double threshold, std::size_t i) const
260 {
261  std::size_t nr_p = 0;
262  const __m128 a_vec = _mm_set1_ps (model_coefficients[0]);
263  const __m128 b_vec = _mm_set1_ps (model_coefficients[1]);
264  const __m128 c_vec = _mm_set1_ps (model_coefficients[2]);
265  const __m128 d_vec = _mm_set1_ps (model_coefficients[3]);
266  const __m128 threshold_vec = _mm_set1_ps (threshold);
267  const __m128 abs_help = _mm_set1_ps (-0.0F); // -0.0F (negative zero) means that all bits are 0, only the sign bit is 1
268  __m128i res = _mm_set1_epi32(0); // This corresponds to nr_p: 4 32bit integers that, summed together, hold the number of inliers
269  for (; (i + 4) <= indices_->size (); i += 4)
270  {
271  const __m128 mask = _mm_cmplt_ps (dist4 (i, a_vec, b_vec, c_vec, d_vec, abs_help), threshold_vec); // The mask contains 1 bits if the corresponding points are inliers, else 0 bits
272  res = _mm_add_epi32 (res, _mm_and_si128 (_mm_set1_epi32 (1), _mm_castps_si128 (mask))); // The latter part creates a vector with ones (as 32bit integers) where the points are inliers
273  //const int res = _mm_movemask_ps (mask);
274  //if (res & 1) nr_p++;
275  //if (res & 2) nr_p++;
276  //if (res & 4) nr_p++;
277  //if (res & 8) nr_p++;
278  }
279  nr_p += _mm_extract_epi32 (res, 0);
280  nr_p += _mm_extract_epi32 (res, 1);
281  nr_p += _mm_extract_epi32 (res, 2);
282  nr_p += _mm_extract_epi32 (res, 3);
283 
284  // Process the remaining points (at most 3)
285  nr_p += countWithinDistanceStandard(model_coefficients, threshold, i);
286  return (nr_p);
287 }
288 #endif
289 
290 //////////////////////////////////////////////////////////////////////////
291 #if defined (__AVX__) && defined (__AVX2__)
292 template <typename PointT> std::size_t
294  const Eigen::VectorXf &model_coefficients, const double threshold, std::size_t i) const
295 {
296  std::size_t nr_p = 0;
297  const __m256 a_vec = _mm256_set1_ps (model_coefficients[0]);
298  const __m256 b_vec = _mm256_set1_ps (model_coefficients[1]);
299  const __m256 c_vec = _mm256_set1_ps (model_coefficients[2]);
300  const __m256 d_vec = _mm256_set1_ps (model_coefficients[3]);
301  const __m256 threshold_vec = _mm256_set1_ps (threshold);
302  const __m256 abs_help = _mm256_set1_ps (-0.0F); // -0.0F (negative zero) means that all bits are 0, only the sign bit is 1
303  __m256i res = _mm256_set1_epi32(0); // This corresponds to nr_p: 8 32bit integers that, summed together, hold the number of inliers
304  for (; (i + 8) <= indices_->size (); i += 8)
305  {
306  const __m256 mask = _mm256_cmp_ps (dist8 (i, a_vec, b_vec, c_vec, d_vec, abs_help), threshold_vec, _CMP_LT_OQ); // The mask contains 1 bits if the corresponding points are inliers, else 0 bits
307  res = _mm256_add_epi32 (res, _mm256_and_si256 (_mm256_set1_epi32 (1), _mm256_castps_si256 (mask))); // The latter part creates a vector with ones (as 32bit integers) where the points are inliers
308  //const int res = _mm256_movemask_ps (mask);
309  //if (res & 1) nr_p++;
310  //if (res & 2) nr_p++;
311  //if (res & 4) nr_p++;
312  //if (res & 8) nr_p++;
313  //if (res & 16) nr_p++;
314  //if (res & 32) nr_p++;
315  //if (res & 64) nr_p++;
316  //if (res & 128) nr_p++;
317  }
318  nr_p += _mm256_extract_epi32 (res, 0);
319  nr_p += _mm256_extract_epi32 (res, 1);
320  nr_p += _mm256_extract_epi32 (res, 2);
321  nr_p += _mm256_extract_epi32 (res, 3);
322  nr_p += _mm256_extract_epi32 (res, 4);
323  nr_p += _mm256_extract_epi32 (res, 5);
324  nr_p += _mm256_extract_epi32 (res, 6);
325  nr_p += _mm256_extract_epi32 (res, 7);
326 
327  // Process the remaining points (at most 7)
328  nr_p += countWithinDistanceStandard(model_coefficients, threshold, i);
329  return (nr_p);
330 }
331 #endif
332 
333 //////////////////////////////////////////////////////////////////////////
334 template <typename PointT> void
336  const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
337 {
338  // Needs a valid set of model coefficients
339  if (!isModelValid (model_coefficients))
340  {
341  PCL_ERROR ("[pcl::SampleConsensusModelPlane::optimizeModelCoefficients] Given model is invalid!\n");
342  optimized_coefficients = model_coefficients;
343  return;
344  }
345 
346  // Need more than the minimum sample size to make a difference
347  if (inliers.size () <= sample_size_)
348  {
349  PCL_ERROR ("[pcl::SampleConsensusModelPlane::optimizeModelCoefficients] Not enough inliers found to optimize model coefficients (%lu)! Returning the same coefficients.\n", inliers.size ());
350  optimized_coefficients = model_coefficients;
351  return;
352  }
353 
354  Eigen::Vector4f plane_parameters;
355 
356  // Use Least-Squares to fit the plane through all the given sample points and find out its coefficients
357  EIGEN_ALIGN16 Eigen::Matrix3f covariance_matrix;
358  Eigen::Vector4f xyz_centroid;
359 
360  computeMeanAndCovarianceMatrix (*input_, inliers, covariance_matrix, xyz_centroid);
361 
362  // Compute the model coefficients
363  EIGEN_ALIGN16 Eigen::Vector3f::Scalar eigen_value;
364  EIGEN_ALIGN16 Eigen::Vector3f eigen_vector;
365  pcl::eigen33 (covariance_matrix, eigen_value, eigen_vector);
366 
367  // Hessian form (D = nc . p_plane (centroid here) + p)
368  optimized_coefficients.resize (model_size_);
369  optimized_coefficients[0] = eigen_vector [0];
370  optimized_coefficients[1] = eigen_vector [1];
371  optimized_coefficients[2] = eigen_vector [2];
372  optimized_coefficients[3] = 0.0f;
373  optimized_coefficients[3] = -1.0f * optimized_coefficients.dot (xyz_centroid);
374 
375  // Make sure it results in a valid model
376  if (!isModelValid (optimized_coefficients))
377  {
378  optimized_coefficients = model_coefficients;
379  }
380 }
381 
382 //////////////////////////////////////////////////////////////////////////
383 template <typename PointT> void
385  const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
386 {
387  // Needs a valid set of model coefficients
388  if (!isModelValid (model_coefficients))
389  {
390  PCL_ERROR ("[pcl::SampleConsensusModelPlane::projectPoints] Given model is invalid!\n");
391  return;
392  }
393 
394  projected_points.header = input_->header;
395  projected_points.is_dense = input_->is_dense;
396 
397  Eigen::Vector4f mc (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
398 
399  // normalize the vector perpendicular to the plane...
400  mc.normalize ();
401  // ... and store the resulting normal as a local copy of the model coefficients
402  Eigen::Vector4f tmp_mc = model_coefficients;
403  tmp_mc[0] = mc[0];
404  tmp_mc[1] = mc[1];
405  tmp_mc[2] = mc[2];
406 
407  // Copy all the data fields from the input cloud to the projected one?
408  if (copy_data_fields)
409  {
410  // Allocate enough space and copy the basics
411  projected_points.resize (input_->size ());
412  projected_points.width = input_->width;
413  projected_points.height = input_->height;
414 
415  using FieldList = typename pcl::traits::fieldList<PointT>::type;
416  // Iterate over each point
417  for (std::size_t i = 0; i < input_->size (); ++i)
418  // Iterate over each dimension
419  pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
420 
421  // Iterate through the 3d points and calculate the distances from them to the plane
422  for (const auto &inlier : inliers)
423  {
424  // Calculate the distance from the point to the plane
425  Eigen::Vector4f p ((*input_)[inlier].x,
426  (*input_)[inlier].y,
427  (*input_)[inlier].z,
428  1);
429  // use normalized coefficients to calculate the scalar projection
430  float distance_to_plane = tmp_mc.dot (p);
431 
432  pcl::Vector4fMap pp = projected_points[inlier].getVector4fMap ();
433  pp.matrix () = p - mc * distance_to_plane; // mc[3] = 0, therefore the 3rd coordinate is safe
434  }
435  }
436  else
437  {
438  // Allocate enough space and copy the basics
439  projected_points.resize (inliers.size ());
440  projected_points.width = inliers.size ();
441  projected_points.height = 1;
442 
443  using FieldList = typename pcl::traits::fieldList<PointT>::type;
444  // Iterate over each point
445  for (std::size_t i = 0; i < inliers.size (); ++i)
446  {
447  // Iterate over each dimension
448  pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
449  }
450 
451  // Iterate through the 3d points and calculate the distances from them to the plane
452  for (std::size_t i = 0; i < inliers.size (); ++i)
453  {
454  // Calculate the distance from the point to the plane
455  Eigen::Vector4f p ((*input_)[inliers[i]].x,
456  (*input_)[inliers[i]].y,
457  (*input_)[inliers[i]].z,
458  1.0f);
459  // use normalized coefficients to calculate the scalar projection
460  float distance_to_plane = tmp_mc.dot (p);
461 
462  pcl::Vector4fMap pp = projected_points[i].getVector4fMap ();
463  pp.matrix () = p - mc * distance_to_plane; // mc[3] = 0, therefore the 3rd coordinate is safe
464  }
465  }
466 }
467 
468 //////////////////////////////////////////////////////////////////////////
469 template <typename PointT> bool
471  const std::set<index_t> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
472 {
473  // Needs a valid set of model coefficients
474  if (!isModelValid (model_coefficients))
475  {
476  PCL_ERROR ("[pcl::SampleConsensusModelPlane::doSamplesVerifyModel] Given model is invalid!\n");
477  return (false);
478  }
479 
480  for (const auto &index : indices)
481  {
482  Eigen::Vector4f pt ((*input_)[index].x,
483  (*input_)[index].y,
484  (*input_)[index].z,
485  1.0f);
486  if (std::abs (model_coefficients.dot (pt)) > threshold)
487  {
488  return (false);
489  }
490  }
491 
492  return (true);
493 }
494 
495 #define PCL_INSTANTIATE_SampleConsensusModelPlane(T) template class PCL_EXPORTS pcl::SampleConsensusModelPlane<T>;
496 
497 #endif // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_PLANE_H_
498 
pcl::computeMeanAndCovarianceMatrix
unsigned int computeMeanAndCovarianceMatrix(const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > &centroid)
Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single lo...
Definition: centroid.hpp:485
pcl::PointCloud::height
std::uint32_t height
The point cloud height (if organized as an image-structure).
Definition: point_cloud.h:394
pcl::SampleConsensusModelPlane::selectWithinDistance
void selectWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers) override
Select all the points which respect the given model coefficients as inliers.
Definition: sac_model_plane.hpp:176
pcl::SampleConsensusModelPlane::countWithinDistance
std::size_t countWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold) const override
Count all the points which respect the given model coefficients as inliers.
Definition: sac_model_plane.hpp:214
pcl::geometry::distance
float distance(const PointT &p1, const PointT &p2)
Definition: geometry.h:60
pcl::SampleConsensusModelPlane
SampleConsensusModelPlane defines a model for 3D plane segmentation.
Definition: sac_model_plane.h:135
pcl::NdConcatenateFunctor
Helper functor structure for concatenate.
Definition: concatenate.h:49
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: distances.h:55
pcl::eigen33
void eigen33(const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
determines the eigenvector and eigenvalue of the smallest eigenvalue of the symmetric positive semi d...
Definition: eigen.hpp:296
pcl::SampleConsensusModelPlane::countWithinDistanceStandard
std::size_t countWithinDistanceStandard(const Eigen::VectorXf &model_coefficients, const double threshold, std::size_t i=0) const
This implementation uses no SIMD instructions.
Definition: sac_model_plane.hpp:234
pcl::SampleConsensusModelPlane::projectPoints
void projectPoints(const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true) const override
Create a new point cloud with inliers projected onto the plane model.
Definition: sac_model_plane.hpp:384
pcl::PointCloud::width
std::uint32_t width
The point cloud width (if organized as an image-structure).
Definition: point_cloud.h:392
pcl::SampleConsensusModelPlane::optimizeModelCoefficients
void optimizeModelCoefficients(const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const override
Recompute the plane coefficients using the given inlier set and return them to the user.
Definition: sac_model_plane.hpp:335
pcl::SampleConsensusModelPlane::computeModelCoefficients
bool computeModelCoefficients(const Indices &samples, Eigen::VectorXf &model_coefficients) const override
Check whether the given index samples can form a valid plane model, compute the model coefficients fr...
Definition: sac_model_plane.hpp:70
pcl::Array4fMapConst
const Eigen::Map< const Eigen::Array4f, Eigen::Aligned > Array4fMapConst
Definition: point_types.hpp:179
pcl::PointCloud::is_dense
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:397
pcl::PointCloud::resize
void resize(std::size_t count)
Resizes the container to contain count elements.
Definition: point_cloud.h:456
pcl::PointCloud::header
pcl::PCLHeader header
The point cloud header.
Definition: point_cloud.h:386
pcl::Indices
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:131
pcl::SampleConsensusModelPlane::getDistancesToModel
void getDistancesToModel(const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) const override
Compute all distances from the cloud data to a given plane model.
Definition: sac_model_plane.hpp:145
pcl::SampleConsensusModelPlane::doSamplesVerifyModel
bool doSamplesVerifyModel(const std::set< index_t > &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const override
Verify whether a subset of indices verifies the given plane model coefficients.
Definition: sac_model_plane.hpp:470
pcl::Vector4fMap
Eigen::Map< Eigen::Vector4f, Eigen::Aligned > Vector4fMap
Definition: point_types.hpp:182
centroid.h