Point Cloud Library (PCL)  1.11.1-dev
correspondence_estimation.hpp
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40 
41 #ifndef PCL_REGISTRATION_IMPL_CORRESPONDENCE_ESTIMATION_H_
42 #define PCL_REGISTRATION_IMPL_CORRESPONDENCE_ESTIMATION_H_
43 
44 #include <pcl/common/copy_point.h>
45 #include <pcl/common/io.h>
46 
47 namespace pcl {
48 
49 namespace registration {
50 
51 template <typename PointSource, typename PointTarget, typename Scalar>
52 void
54  const PointCloudTargetConstPtr& cloud)
55 {
56  if (cloud->points.empty()) {
57  PCL_ERROR("[pcl::registration::%s::setInputTarget] Invalid or empty point cloud "
58  "dataset given!\n",
59  getClassName().c_str());
60  return;
61  }
62  target_ = cloud;
63 
64  // Set the internal point representation of choice
65  if (point_representation_)
66  tree_->setPointRepresentation(point_representation_);
67 
68  target_cloud_updated_ = true;
69 }
70 
71 template <typename PointSource, typename PointTarget, typename Scalar>
72 bool
74 {
75  if (!target_) {
76  PCL_ERROR("[pcl::registration::%s::compute] No input target dataset was given!\n",
77  getClassName().c_str());
78  return (false);
79  }
80 
81  // Only update target kd-tree if a new target cloud was set
82  if (target_cloud_updated_ && !force_no_recompute_) {
83  // If the target indices have been given via setIndicesTarget
84  if (target_indices_)
85  tree_->setInputCloud(target_, target_indices_);
86  else
87  tree_->setInputCloud(target_);
88 
89  target_cloud_updated_ = false;
90  }
91 
93 }
94 
95 template <typename PointSource, typename PointTarget, typename Scalar>
96 bool
98 {
99  // Only update source kd-tree if a new target cloud was set
100  if (source_cloud_updated_ && !force_no_recompute_reciprocal_) {
101  if (point_representation_)
102  tree_reciprocal_->setPointRepresentation(point_representation_);
103  // If the target indices have been given via setIndicesTarget
104  if (indices_)
105  tree_reciprocal_->setInputCloud(getInputSource(), getIndicesSource());
106  else
107  tree_reciprocal_->setInputCloud(getInputSource());
108 
109  source_cloud_updated_ = false;
110  }
111 
112  return (true);
113 }
114 
115 template <typename PointSource, typename PointTarget, typename Scalar>
116 void
118  pcl::Correspondences& correspondences, double max_distance)
119 {
120  if (!initCompute())
121  return;
122 
123  double max_dist_sqr = max_distance * max_distance;
124 
125  correspondences.resize(indices_->size());
126 
127  pcl::Indices index(1);
128  std::vector<float> distance(1);
129  pcl::Correspondence corr;
130  unsigned int nr_valid_correspondences = 0;
131 
132  // Check if the template types are the same. If true, avoid a copy.
133  // Both point types MUST be registered using the POINT_CLOUD_REGISTER_POINT_STRUCT
134  // macro!
135  if (isSamePointType<PointSource, PointTarget>()) {
136  // Iterate over the input set of source indices
137  for (const auto& idx : (*indices_)) {
138  tree_->nearestKSearch((*input_)[idx], 1, index, distance);
139  if (distance[0] > max_dist_sqr)
140  continue;
141 
142  corr.index_query = idx;
143  corr.index_match = index[0];
144  corr.distance = distance[0];
145  correspondences[nr_valid_correspondences++] = corr;
146  }
147  }
148  else {
149  PointTarget pt;
150 
151  // Iterate over the input set of source indices
152  for (const auto& idx : (*indices_)) {
153  // Copy the source data to a target PointTarget format so we can search in the
154  // tree
155  copyPoint((*input_)[idx], pt);
156 
157  tree_->nearestKSearch(pt, 1, index, distance);
158  if (distance[0] > max_dist_sqr)
159  continue;
160 
161  corr.index_query = idx;
162  corr.index_match = index[0];
163  corr.distance = distance[0];
164  correspondences[nr_valid_correspondences++] = corr;
165  }
166  }
167  correspondences.resize(nr_valid_correspondences);
168  deinitCompute();
169 }
170 
171 template <typename PointSource, typename PointTarget, typename Scalar>
172 void
175  double max_distance)
176 {
177  if (!initCompute())
178  return;
179 
180  // setup tree for reciprocal search
181  // Set the internal point representation of choice
182  if (!initComputeReciprocal())
183  return;
184  double max_dist_sqr = max_distance * max_distance;
185 
186  correspondences.resize(indices_->size());
187  pcl::Indices index(1);
188  std::vector<float> distance(1);
189  pcl::Indices index_reciprocal(1);
190  std::vector<float> distance_reciprocal(1);
191  pcl::Correspondence corr;
192  unsigned int nr_valid_correspondences = 0;
193  int target_idx = 0;
194 
195  // Check if the template types are the same. If true, avoid a copy.
196  // Both point types MUST be registered using the POINT_CLOUD_REGISTER_POINT_STRUCT
197  // macro!
198  if (isSamePointType<PointSource, PointTarget>()) {
199  // Iterate over the input set of source indices
200  for (const auto& idx : (*indices_)) {
201  tree_->nearestKSearch((*input_)[idx], 1, index, distance);
202  if (distance[0] > max_dist_sqr)
203  continue;
204 
205  target_idx = index[0];
206 
207  tree_reciprocal_->nearestKSearch(
208  (*target_)[target_idx], 1, index_reciprocal, distance_reciprocal);
209  if (distance_reciprocal[0] > max_dist_sqr || idx != index_reciprocal[0])
210  continue;
211 
212  corr.index_query = idx;
213  corr.index_match = index[0];
214  corr.distance = distance[0];
215  correspondences[nr_valid_correspondences++] = corr;
216  }
217  }
218  else {
219  PointTarget pt_src;
220  PointSource pt_tgt;
221 
222  // Iterate over the input set of source indices
223  for (const auto& idx : (*indices_)) {
224  // Copy the source data to a target PointTarget format so we can search in the
225  // tree
226  copyPoint((*input_)[idx], pt_src);
227 
228  tree_->nearestKSearch(pt_src, 1, index, distance);
229  if (distance[0] > max_dist_sqr)
230  continue;
231 
232  target_idx = index[0];
233 
234  // Copy the target data to a target PointSource format so we can search in the
235  // tree_reciprocal
236  copyPoint((*target_)[target_idx], pt_tgt);
237 
238  tree_reciprocal_->nearestKSearch(
239  pt_tgt, 1, index_reciprocal, distance_reciprocal);
240  if (distance_reciprocal[0] > max_dist_sqr || idx != index_reciprocal[0])
241  continue;
242 
243  corr.index_query = idx;
244  corr.index_match = index[0];
245  corr.distance = distance[0];
246  correspondences[nr_valid_correspondences++] = corr;
247  }
248  }
249  correspondences.resize(nr_valid_correspondences);
250  deinitCompute();
251 }
252 
253 } // namespace registration
254 } // namespace pcl
255 
256 //#define PCL_INSTANTIATE_CorrespondenceEstimation(T,U) template class PCL_EXPORTS
257 // pcl::registration::CorrespondenceEstimation<T,U>;
258 
259 #endif /* PCL_REGISTRATION_IMPL_CORRESPONDENCE_ESTIMATION_H_ */
pcl
Definition: convolution.h:46
pcl::geometry::distance
float distance(const PointT &p1, const PointT &p2)
Definition: geometry.h:60
pcl::Correspondence::distance
float distance
Definition: correspondence.h:69
pcl::registration::CorrespondenceEstimationBase::setInputTarget
void setInputTarget(const PointCloudTargetConstPtr &cloud)
Provide a pointer to the input target (e.g., the point cloud that we want to align the input source t...
Definition: correspondence_estimation.hpp:53
pcl::registration::CorrespondenceEstimationBase::initCompute
bool initCompute()
Internal computation initialization.
Definition: correspondence_estimation.hpp:73
pcl::PCLBase
PCL base class.
Definition: pcl_base.h:69
pcl::registration::CorrespondenceEstimationBase< PointSource, PointTarget, float >::PointCloudTargetConstPtr
typename PointCloudTarget::ConstPtr PointCloudTargetConstPtr
Definition: correspondence_estimation.h:85
pcl::registration::CorrespondenceEstimationBase::initComputeReciprocal
bool initComputeReciprocal()
Internal computation initialization for reciprocal correspondences.
Definition: correspondence_estimation.hpp:97
pcl::copyPoint
void copyPoint(const PointInT &point_in, PointOutT &point_out)
Copy the fields of a source point into a target point.
Definition: copy_point.hpp:137
pcl::registration::CorrespondenceEstimation::determineCorrespondences
void determineCorrespondences(pcl::Correspondences &correspondences, double max_distance=std::numeric_limits< double >::max()) override
Determine the correspondences between input and target cloud.
Definition: correspondence_estimation.hpp:117
pcl::Indices
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
pcl::Correspondence::index_match
index_t index_match
Index of the matching (target) point.
Definition: correspondence.h:65
pcl::Correspondences
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
Definition: correspondence.h:89
pcl::Correspondence::index_query
index_t index_query
Index of the query (source) point.
Definition: correspondence.h:63
pcl::registration::CorrespondenceEstimation::determineReciprocalCorrespondences
void determineReciprocalCorrespondences(pcl::Correspondences &correspondences, double max_distance=std::numeric_limits< double >::max()) override
Determine the reciprocal correspondences between input and target cloud.
Definition: correspondence_estimation.hpp:174
pcl::Correspondence
Correspondence represents a match between two entities (e.g., points, descriptors,...
Definition: correspondence.h:60