Point Cloud Library (PCL)  1.12.1-dev
sac_model_registration.hpp
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40 
41 #ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_REGISTRATION_H_
42 #define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_REGISTRATION_H_
43 
44 #include <pcl/sample_consensus/sac_model_registration.h>
45 
46 //////////////////////////////////////////////////////////////////////////
47 template <typename PointT> bool
49 {
50  if (samples.size () != sample_size_)
51  {
52  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
53  return (false);
54  }
55  using namespace pcl::common;
56  using namespace pcl::traits;
57 
58  PointT p10 = (*input_)[samples[1]] - (*input_)[samples[0]];
59  PointT p20 = (*input_)[samples[2]] - (*input_)[samples[0]];
60  PointT p21 = (*input_)[samples[2]] - (*input_)[samples[1]];
61 
62  return ((p10.x * p10.x + p10.y * p10.y + p10.z * p10.z) > sample_dist_thresh_ &&
63  (p20.x * p20.x + p20.y * p20.y + p20.z * p20.z) > sample_dist_thresh_ &&
64  (p21.x * p21.x + p21.y * p21.y + p21.z * p21.z) > sample_dist_thresh_);
65 }
66 
67 //////////////////////////////////////////////////////////////////////////
68 template <typename PointT> bool
69 pcl::SampleConsensusModelRegistration<PointT>::computeModelCoefficients (const Indices &samples, Eigen::VectorXf &model_coefficients) const
70 {
71  if (!target_)
72  {
73  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::computeModelCoefficients] No target dataset given!\n");
74  return (false);
75  }
76  // Need 3 samples
77  if (samples.size () != sample_size_)
78  {
79  return (false);
80  }
81 
82  Indices indices_tgt (3);
83  for (int i = 0; i < 3; ++i)
84  {
85  const auto it = correspondences_.find (samples[i]);
86  if (it == correspondences_.cend ())
87  {
88  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::computeModelCoefficients] Element with key %i is not in map (map contains %lu elements).\n",
89  samples[i], correspondences_.size ());
90  return (false);
91  }
92  indices_tgt[i] = it->second;
93  }
94 
95  estimateRigidTransformationSVD (*input_, samples, *target_, indices_tgt, model_coefficients);
96  return (true);
97 }
98 
99 //////////////////////////////////////////////////////////////////////////
100 template <typename PointT> void
101 pcl::SampleConsensusModelRegistration<PointT>::getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
102 {
103  if (indices_->size () != indices_tgt_->size ())
104  {
105  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::getDistancesToModel] Number of source indices (%lu) differs than number of target indices (%lu)!\n", indices_->size (), indices_tgt_->size ());
106  distances.clear ();
107  return;
108  }
109  if (!target_)
110  {
111  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::getDistanceToModel] No target dataset given!\n");
112  return;
113  }
114  // Check if the model is valid given the user constraints
115  if (!isModelValid (model_coefficients))
116  {
117  distances.clear ();
118  return;
119  }
120  distances.resize (indices_->size ());
121 
122  // Get the 4x4 transformation
123  Eigen::Matrix4f transform;
124  transform.row (0).matrix () = model_coefficients.segment<4>(0);
125  transform.row (1).matrix () = model_coefficients.segment<4>(4);
126  transform.row (2).matrix () = model_coefficients.segment<4>(8);
127  transform.row (3).matrix () = model_coefficients.segment<4>(12);
128 
129  for (std::size_t i = 0; i < indices_->size (); ++i)
130  {
131  Eigen::Vector4f pt_src ((*input_)[(*indices_)[i]].x,
132  (*input_)[(*indices_)[i]].y,
133  (*input_)[(*indices_)[i]].z, 1.0f);
134  Eigen::Vector4f pt_tgt ((*target_)[(*indices_tgt_)[i]].x,
135  (*target_)[(*indices_tgt_)[i]].y,
136  (*target_)[(*indices_tgt_)[i]].z, 1.0f);
137 
138  Eigen::Vector4f p_tr (transform * pt_src);
139  // Calculate the distance from the transformed point to its correspondence
140  // need to compute the real norm here to keep MSAC and friends general
141  distances[i] = (p_tr - pt_tgt).norm ();
142  }
143 }
144 
145 //////////////////////////////////////////////////////////////////////////
146 template <typename PointT> void
147 pcl::SampleConsensusModelRegistration<PointT>::selectWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
148 {
149  if (indices_->size () != indices_tgt_->size ())
150  {
151  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::selectWithinDistance] Number of source indices (%lu) differs than number of target indices (%lu)!\n", indices_->size (), indices_tgt_->size ());
152  inliers.clear ();
153  return;
154  }
155  if (!target_)
156  {
157  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::selectWithinDistance] No target dataset given!\n");
158  return;
159  }
160 
161  double thresh = threshold * threshold;
162 
163  // Check if the model is valid given the user constraints
164  if (!isModelValid (model_coefficients))
165  {
166  inliers.clear ();
167  return;
168  }
169 
170  inliers.clear ();
171  error_sqr_dists_.clear ();
172  inliers.reserve (indices_->size ());
173  error_sqr_dists_.reserve (indices_->size ());
174 
175  Eigen::Matrix4f transform;
176  transform.row (0).matrix () = model_coefficients.segment<4>(0);
177  transform.row (1).matrix () = model_coefficients.segment<4>(4);
178  transform.row (2).matrix () = model_coefficients.segment<4>(8);
179  transform.row (3).matrix () = model_coefficients.segment<4>(12);
180 
181  for (std::size_t i = 0; i < indices_->size (); ++i)
182  {
183  Eigen::Vector4f pt_src ((*input_)[(*indices_)[i]].x,
184  (*input_)[(*indices_)[i]].y,
185  (*input_)[(*indices_)[i]].z, 1);
186  Eigen::Vector4f pt_tgt ((*target_)[(*indices_tgt_)[i]].x,
187  (*target_)[(*indices_tgt_)[i]].y,
188  (*target_)[(*indices_tgt_)[i]].z, 1);
189 
190  Eigen::Vector4f p_tr (transform * pt_src);
191 
192  float distance = (p_tr - pt_tgt).squaredNorm ();
193  // Calculate the distance from the transformed point to its correspondence
194  if (distance < thresh)
195  {
196  inliers.push_back ((*indices_)[i]);
197  error_sqr_dists_.push_back (static_cast<double> (distance));
198  }
199  }
200 }
201 
202 //////////////////////////////////////////////////////////////////////////
203 template <typename PointT> std::size_t
205  const Eigen::VectorXf &model_coefficients, const double threshold) const
206 {
207  if (indices_->size () != indices_tgt_->size ())
208  {
209  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::countWithinDistance] Number of source indices (%lu) differs than number of target indices (%lu)!\n", indices_->size (), indices_tgt_->size ());
210  return (0);
211  }
212  if (!target_)
213  {
214  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::countWithinDistance] No target dataset given!\n");
215  return (0);
216  }
217 
218  double thresh = threshold * threshold;
219 
220  // Check if the model is valid given the user constraints
221  if (!isModelValid (model_coefficients))
222  {
223  return (0);
224  }
225 
226  Eigen::Matrix4f transform;
227  transform.row (0).matrix () = model_coefficients.segment<4>(0);
228  transform.row (1).matrix () = model_coefficients.segment<4>(4);
229  transform.row (2).matrix () = model_coefficients.segment<4>(8);
230  transform.row (3).matrix () = model_coefficients.segment<4>(12);
231 
232  std::size_t nr_p = 0;
233  for (std::size_t i = 0; i < indices_->size (); ++i)
234  {
235  Eigen::Vector4f pt_src ((*input_)[(*indices_)[i]].x,
236  (*input_)[(*indices_)[i]].y,
237  (*input_)[(*indices_)[i]].z, 1);
238  Eigen::Vector4f pt_tgt ((*target_)[(*indices_tgt_)[i]].x,
239  (*target_)[(*indices_tgt_)[i]].y,
240  (*target_)[(*indices_tgt_)[i]].z, 1);
241 
242  Eigen::Vector4f p_tr (transform * pt_src);
243  // Calculate the distance from the transformed point to its correspondence
244  if ((p_tr - pt_tgt).squaredNorm () < thresh)
245  nr_p++;
246  }
247  return (nr_p);
248 }
249 
250 //////////////////////////////////////////////////////////////////////////
251 template <typename PointT> void
252 pcl::SampleConsensusModelRegistration<PointT>::optimizeModelCoefficients (const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
253 {
254  if (indices_->size () != indices_tgt_->size ())
255  {
256  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::optimizeModelCoefficients] Number of source indices (%lu) differs than number of target indices (%lu)!\n", indices_->size (), indices_tgt_->size ());
257  optimized_coefficients = model_coefficients;
258  return;
259  }
260 
261  // Check if the model is valid given the user constraints
262  if (!isModelValid (model_coefficients) || !target_)
263  {
264  optimized_coefficients = model_coefficients;
265  return;
266  }
267 
268  Indices indices_src (inliers.size ());
269  Indices indices_tgt (inliers.size ());
270  for (std::size_t i = 0; i < inliers.size (); ++i)
271  {
272  indices_src[i] = inliers[i];
273  const auto it = correspondences_.find (indices_src[i]);
274  if (it == correspondences_.cend ())
275  {
276  PCL_ERROR ("[pcl::SampleConsensusModelRegistration::optimizeModelCoefficients] Element with key %i is not in map (map contains %lu elements).\n",
277  indices_src[i], correspondences_.size ());
278  optimized_coefficients = model_coefficients;
279  return;
280  }
281  indices_tgt[i] = it->second;
282  }
283 
284  estimateRigidTransformationSVD (*input_, indices_src, *target_, indices_tgt, optimized_coefficients);
285 }
286 
287 //////////////////////////////////////////////////////////////////////////
288 template <typename PointT> void
290  const pcl::PointCloud<PointT> &cloud_src,
291  const Indices &indices_src,
292  const pcl::PointCloud<PointT> &cloud_tgt,
293  const Indices &indices_tgt,
294  Eigen::VectorXf &transform) const
295 {
296  transform.resize (16);
297 
298  Eigen::Matrix<double, 3, Eigen::Dynamic> src (3, indices_src.size ());
299  Eigen::Matrix<double, 3, Eigen::Dynamic> tgt (3, indices_tgt.size ());
300 
301  for (std::size_t i = 0; i < indices_src.size (); ++i)
302  {
303  src (0, i) = cloud_src[indices_src[i]].x;
304  src (1, i) = cloud_src[indices_src[i]].y;
305  src (2, i) = cloud_src[indices_src[i]].z;
306 
307  tgt (0, i) = cloud_tgt[indices_tgt[i]].x;
308  tgt (1, i) = cloud_tgt[indices_tgt[i]].y;
309  tgt (2, i) = cloud_tgt[indices_tgt[i]].z;
310  }
311 
312  // Call Umeyama directly from Eigen
313  Eigen::Matrix4d transformation_matrix = pcl::umeyama (src, tgt, false);
314 
315  // Return the correct transformation
316  transform.segment<4> (0).matrix () = transformation_matrix.cast<float> ().row (0);
317  transform.segment<4> (4).matrix () = transformation_matrix.cast<float> ().row (1);
318  transform.segment<4> (8).matrix () = transformation_matrix.cast<float> ().row (2);
319  transform.segment<4> (12).matrix () = transformation_matrix.cast<float> ().row (3);
320 }
321 
322 #define PCL_INSTANTIATE_SampleConsensusModelRegistration(T) template class PCL_EXPORTS pcl::SampleConsensusModelRegistration<T>;
323 
324 #endif // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_REGISTRATION_H_
325 
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: point_cloud.h:173
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.
bool computeModelCoefficients(const Indices &samples, Eigen::VectorXf &model_coefficients) const override
Compute a 4x4 rigid transformation matrix from the samples given.
void getDistancesToModel(const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) const override
Compute all distances from the transformed points to their correspondences.
void estimateRigidTransformationSVD(const pcl::PointCloud< PointT > &cloud_src, const Indices &indices_src, const pcl::PointCloud< PointT > &cloud_tgt, const Indices &indices_tgt, Eigen::VectorXf &transform) const
Estimate a rigid transformation between a source and a target point cloud using an SVD closed-form so...
bool isSampleGood(const Indices &samples) const override
Check if a sample of indices results in a good sample of points indices.
void optimizeModelCoefficients(const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const override
Recompute the 4x4 transformation using the given inlier set.
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.
float distance(const PointT &p1, const PointT &p2)
Definition: geometry.h:60
Eigen::internal::umeyama_transform_matrix_type< Derived, OtherDerived >::type umeyama(const Eigen::MatrixBase< Derived > &src, const Eigen::MatrixBase< OtherDerived > &dst, bool with_scaling=false)
Returns the transformation between two point sets.
Definition: eigen.hpp:660
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
A point structure representing Euclidean xyz coordinates, and the RGB color.