Registration represents the base registration class. All 3D registration methods should inherit from this class. More...
#include <registration.h>
Classes | |
| class | FeatureContainer |
| An inner class containing pointers to the source and target feature clouds along with the KdTree and the parameters needed to perform the correspondence search. This class extends FeatureContainerInterface, which contains abstract methods for any methods that do not depend on the FeatureType --- these methods can thus be called from a pointer to FeatureContainerInterface without casting to the derived class. More... | |
| class | FeatureContainerInterface |
Public Types | |
| typedef std::map< std::string, boost::shared_ptr < FeatureContainerInterface > > | FeaturesMap |
| typedef pcl::KdTree< PointTarget > | KdTree |
| typedef pcl::KdTree < PointTarget >::Ptr | KdTreePtr |
| typedef pcl::PointCloud < PointSource > | PointCloudSource |
| typedef PointCloudSource::ConstPtr | PointCloudSourceConstPtr |
| typedef PointCloudSource::Ptr | PointCloudSourcePtr |
| typedef pcl::PointCloud < PointTarget > | PointCloudTarget |
| typedef PointCloudTarget::ConstPtr | PointCloudTargetConstPtr |
| typedef PointCloudTarget::Ptr | PointCloudTargetPtr |
| typedef KdTree::PointRepresentationConstPtr | PointRepresentationConstPtr |
Public Member Functions | |
| void | align (PointCloudSource &output) |
| Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output. | |
| Eigen::Matrix4f | getFinalTransformation () |
| Get the final transformation matrix estimated by the registration method. | |
| double | getFitnessScore (double max_range=std::numeric_limits< double >::max()) |
| Obtain the fitness score (e.g., sum of squared distances from the source to the target). | |
| PointCloudTargetConstPtr const | getInputTarget () |
| Get a pointer to the input point cloud dataset target. | |
| Eigen::Matrix4f | getLastIncrementalTransformation () |
| Get the last incremental transformation matrix estimated by the registration method. | |
| double | getMaxCorrespondenceDistance () |
| Get the maximum distance threshold between two correspondent points in source <-> target. If the distance is larger than this threshold, the points will be ignored in the alignment process. | |
| int | getMaximumIterations () |
| Get the maximum number of iterations the internal optimization should run for, as set by the user. | |
| double | getRANSACOutlierRejectionThreshold () |
| Get the inlier distance threshold for the internal outlier rejection loop as set by the user. | |
| template<typename FeatureType > | |
| pcl::PointCloud< FeatureType > ::ConstPtr | getSourceFeature (std::string key) |
| Get a pointer to the source cloud's feature descriptors, specified by the given key. | |
| template<typename FeatureType > | |
| pcl::PointCloud< FeatureType > ::ConstPtr | getTargetFeature (std::string key) |
| Get a pointer to the source cloud's feature descriptors, specified by the given key. | |
| double | getTransformationEpsilon () |
| Get the transformation epsilon (maximum allowable difference between two consecutive transformations) as set by the user. | |
| bool | hasConverged () |
| Return the state of convergence after the last align run. | |
| Registration () | |
| Empty constructor. | |
| virtual 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 to). | |
| template<typename FeatureType > | |
| void | setKSearch (const typename pcl::KdTree< FeatureType >::Ptr &tree, int k, std::string key) |
| Use k-nearest-neighbors as the search method when finding correspondences for the feature associated with the provided key. | |
| void | setMaxCorrespondenceDistance (double distance_threshold) |
| Set the maximum distance threshold between two correspondent points in source <-> target. If the distance is larger than this threshold, the points will be ignored in the alignment process. | |
| void | setMaximumIterations (int nr_iterations) |
| Set the maximum number of iterations the internal optimization should run for. | |
| void | setPointRepresentation (const PointRepresentationConstPtr &point_representation) |
| Provide a boost shared pointer to the PointRepresentation to be used when comparing points. | |
| template<typename FeatureType > | |
| void | setRadiusSearch (const typename pcl::KdTree< FeatureType >::Ptr &tree, float r, std::string key) |
| Use radius-search as the search method when finding correspondences for the feature associated with the provided key. | |
| void | setRANSACOutlierRejectionThreshold (double inlier_threshold) |
| Set the inlier distance threshold for the internal RANSAC outlier rejection loop. | |
| template<typename FeatureType > | |
| void | setSourceFeature (const typename pcl::PointCloud< FeatureType >::ConstPtr &source_feature, std::string key) |
| Provide a pointer to a cloud of feature descriptors associated with the source point cloud. | |
| template<typename FeatureType > | |
| void | setTargetFeature (const typename pcl::PointCloud< FeatureType >::ConstPtr &target_feature, std::string key) |
| Provide a pointer to a cloud of feature descriptors associated with the target point cloud. | |
| void | setTransformationEpsilon (double epsilon) |
| Set the transformation epsilon (maximum allowable difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution. | |
Protected Member Functions | |
| void | findFeatureCorrespondences (int index, std::vector< int > &correspondence_indices) |
| Find the indices of the points in the target cloud whose features correspond with the features of the given point in the source cloud. | |
| const std::string & | getClassName () const |
| Abstract class get name method. | |
| bool | hasValidFeatures () |
| Test that all features are valid (i.e., does each key have a valid source cloud, target cloud, and search method). | |
| bool | searchForNeighbors (const PointCloudSource &cloud, int index, std::vector< int > &indices, std::vector< float > &distances) |
| Search for the closest nearest neighbor of a given point. | |
Protected Attributes | |
| bool | converged_ |
| Holds internal convergence state, given user parameters. | |
| double | corr_dist_threshold_ |
| The maximum distance threshold between two correspondent points in source <-> target. If the distance is larger than this threshold, the points will not be ignored in the alignement process. | |
| Eigen::Matrix4f | final_transformation_ |
| The final transformation matrix estimated by the registration method after N iterations. | |
| double | inlier_threshold_ |
| The inlier distance threshold for the internal RANSAC outlier rejection loop. The method considers a point to be an inlier, if the distance between the target data index and the transformed source index is smaller than the given inlier distance threshold. | |
| int | max_iterations_ |
| The maximum number of iterations the internal optimization should run for. | |
| int | min_number_correspondences_ |
| The minimum number of correspondences that the algorithm needs before attempting to estimate the transformation. | |
| int | nr_iterations_ |
| The number of iterations the internal optimization ran for (used internally). | |
| Eigen::Matrix4f | previous_transformation_ |
| The previous transformation matrix estimated by the registration method (used internally). | |
| std::string | reg_name_ |
| The registration method name. | |
| PointCloudTargetConstPtr | target_ |
| The input point cloud dataset target. | |
| Eigen::Matrix4f | transformation_ |
| The transformation matrix estimated by the registration method. | |
| double | transformation_epsilon_ |
| The maximum difference between two consecutive transformations in order to consider convergence (user defined). | |
| KdTreePtr | tree_ |
| A pointer to the spatial search object. | |
Private Member Functions | |
| virtual void | computeTransformation (PointCloudSource &output)=0 |
| Abstract transformation computation method. | |
Private Attributes | |
| FeaturesMap | features_map_ |
| An STL map containing features to use when performing the correspondence search. | |
| PointRepresentationConstPtr | point_representation_ |
| The number of K nearest neighbors to use for each point. | |
Registration represents the base registration class. All 3D registration methods should inherit from this class.
Definition at line 97 of file registration.h.
| typedef std::map<std::string, boost::shared_ptr<FeatureContainerInterface> > pcl::Registration< PointSource, PointTarget >::FeaturesMap |
Definition at line 120 of file registration.h.
| typedef pcl::KdTree<PointTarget> pcl::Registration< PointSource, PointTarget >::KdTree |
Definition at line 107 of file registration.h.
| typedef pcl::KdTree<PointTarget>::Ptr pcl::Registration< PointSource, PointTarget >::KdTreePtr |
Definition at line 108 of file registration.h.
| typedef pcl::PointCloud<PointSource> pcl::Registration< PointSource, PointTarget >::PointCloudSource |
Reimplemented in pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >, pcl::IterativeClosestPoint< PointSource, PointTarget >, and pcl::IterativeClosestPointNonLinear< PointSource, PointTarget >.
Definition at line 110 of file registration.h.
| typedef PointCloudSource::ConstPtr pcl::Registration< PointSource, PointTarget >::PointCloudSourceConstPtr |
Reimplemented in pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >, pcl::IterativeClosestPoint< PointSource, PointTarget >, and pcl::IterativeClosestPointNonLinear< PointSource, PointTarget >.
Definition at line 112 of file registration.h.
| typedef PointCloudSource::Ptr pcl::Registration< PointSource, PointTarget >::PointCloudSourcePtr |
Reimplemented in pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >, pcl::IterativeClosestPoint< PointSource, PointTarget >, and pcl::IterativeClosestPointNonLinear< PointSource, PointTarget >.
Definition at line 111 of file registration.h.
| typedef pcl::PointCloud<PointTarget> pcl::Registration< PointSource, PointTarget >::PointCloudTarget |
Reimplemented in pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >, pcl::IterativeClosestPoint< PointSource, PointTarget >, and pcl::IterativeClosestPointNonLinear< PointSource, PointTarget >.
Definition at line 114 of file registration.h.
| typedef PointCloudTarget::ConstPtr pcl::Registration< PointSource, PointTarget >::PointCloudTargetConstPtr |
Definition at line 116 of file registration.h.
| typedef PointCloudTarget::Ptr pcl::Registration< PointSource, PointTarget >::PointCloudTargetPtr |
Definition at line 115 of file registration.h.
| typedef KdTree::PointRepresentationConstPtr pcl::Registration< PointSource, PointTarget >::PointRepresentationConstPtr |
Definition at line 118 of file registration.h.
| pcl::Registration< PointSource, PointTarget >::Registration | ( | ) | [inline] |
Empty constructor.
Definition at line 123 of file registration.h.
| void pcl::Registration< PointSource, PointTarget >::align | ( | PointCloudSource & | output | ) | [inline] |
Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output.
| output | the resultant input transfomed point cloud dataset |
Definition at line 397 of file registration.hpp.
| virtual void pcl::Registration< PointSource, PointTarget >::computeTransformation | ( | PointCloudSource & | output | ) | [private, pure virtual] |
Abstract transformation computation method.
Implemented in pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >, pcl::IterativeClosestPoint< PointSource, PointTarget >, and pcl::IterativeClosestPointNonLinear< PointSource, PointTarget >.
| void pcl::Registration< PointSource, PointTarget >::findFeatureCorrespondences | ( | int | index, | |
| std::vector< int > & | correspondence_indices | |||
| ) | [inline, protected] |
Find the indices of the points in the target cloud whose features correspond with the features of the given point in the source cloud.
| index | the index of the query point (in the source cloud) | |
| correspondence_indices | the resultant vector of indices representing the query's corresponding features (in the target cloud) |
Definition at line 318 of file registration.hpp.
| const std::string& pcl::Registration< PointSource, PointTarget >::getClassName | ( | ) | const [inline, protected] |
Abstract class get name method.
Definition at line 356 of file registration.h.
| Eigen::Matrix4f pcl::Registration< PointSource, PointTarget >::getFinalTransformation | ( | ) | [inline] |
Get the final transformation matrix estimated by the registration method.
Definition at line 190 of file registration.h.
| double pcl::Registration< PointSource, PointTarget >::getFitnessScore | ( | double | max_range = std::numeric_limits<double>::max () |
) | [inline] |
Obtain the fitness score (e.g., sum of squared distances from the source to the target).
| max_range | maximum allowable distance between a point and its correspondent neighbor in the target (default: double::max) |
Definition at line 356 of file registration.hpp.
| PointCloudTargetConstPtr const pcl::Registration< PointSource, PointTarget >::getInputTarget | ( | ) | [inline] |
Get a pointer to the input point cloud dataset target.
Definition at line 142 of file registration.h.
| Eigen::Matrix4f pcl::Registration< PointSource, PointTarget >::getLastIncrementalTransformation | ( | ) | [inline] |
Get the last incremental transformation matrix estimated by the registration method.
Definition at line 194 of file registration.h.
| double pcl::Registration< PointSource, PointTarget >::getMaxCorrespondenceDistance | ( | ) | [inline] |
Get the maximum distance threshold between two correspondent points in source <-> target. If the distance is larger than this threshold, the points will be ignored in the alignment process.
Definition at line 232 of file registration.h.
| int pcl::Registration< PointSource, PointTarget >::getMaximumIterations | ( | ) | [inline] |
Get the maximum number of iterations the internal optimization should run for, as set by the user.
Definition at line 204 of file registration.h.
| double pcl::Registration< PointSource, PointTarget >::getRANSACOutlierRejectionThreshold | ( | ) | [inline] |
Get the inlier distance threshold for the internal outlier rejection loop as set by the user.
Definition at line 218 of file registration.h.
| pcl::PointCloud< FeatureType >::ConstPtr pcl::Registration< PointSource, PointTarget >::getSourceFeature | ( | std::string | key | ) | [inline] |
Get a pointer to the source cloud's feature descriptors, specified by the given key.
| key | a string that uniquely identifies the feature (must match the key provided by setSourceFeature) |
Definition at line 228 of file registration.hpp.
| pcl::PointCloud< FeatureType >::ConstPtr pcl::Registration< PointSource, PointTarget >::getTargetFeature | ( | std::string | key | ) | [inline] |
Get a pointer to the source cloud's feature descriptors, specified by the given key.
| key | a string that uniquely identifies the feature (must match the key provided by setTargetFeature) |
Definition at line 256 of file registration.hpp.
| double pcl::Registration< PointSource, PointTarget >::getTransformationEpsilon | ( | ) | [inline] |
Get the transformation epsilon (maximum allowable difference between two consecutive transformations) as set by the user.
Definition at line 246 of file registration.h.
| bool pcl::Registration< PointSource, PointTarget >::hasConverged | ( | ) | [inline] |
Return the state of convergence after the last align run.
Definition at line 266 of file registration.h.
| bool pcl::Registration< PointSource, PointTarget >::hasValidFeatures | ( | ) | [inline, protected] |
Test that all features are valid (i.e., does each key have a valid source cloud, target cloud, and search method).
Definition at line 299 of file registration.hpp.
| bool pcl::Registration< PointSource, PointTarget >::searchForNeighbors | ( | const PointCloudSource & | cloud, | |
| int | index, | |||
| std::vector< int > & | indices, | |||
| std::vector< float > & | distances | |||
| ) | [inline, protected] |
Search for the closest nearest neighbor of a given point.
| cloud | the point cloud dataset to use for nearest neighbor search | |
| index | the index of the query point | |
| indices | the resultant vector of indices representing the k-nearest neighbors | |
| distances | the resultant distances from the query point to the k-nearest neighbors |
Definition at line 331 of file registration.h.
| void pcl::Registration< PointSource, PointTarget >::setInputTarget | ( | const PointCloudTargetConstPtr & | cloud | ) | [inline, virtual] |
Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to).
| cloud | the input point cloud target |
Definition at line 195 of file registration.hpp.
| void pcl::Registration< PointSource, PointTarget >::setKSearch | ( | const typename pcl::KdTree< FeatureType >::Ptr & | tree, | |
| int | k, | |||
| std::string | key | |||
| ) | [inline] |
Use k-nearest-neighbors as the search method when finding correspondences for the feature associated with the provided key.
| tree | the KdTree to use to compare features | |
| k | the number of nearest neighbors to return in the correspondence search | |
| key | a string that uniquely identifies the feature |
Definition at line 287 of file registration.hpp.
| void pcl::Registration< PointSource, PointTarget >::setMaxCorrespondenceDistance | ( | double | distance_threshold | ) | [inline] |
Set the maximum distance threshold between two correspondent points in source <-> target. If the distance is larger than this threshold, the points will be ignored in the alignment process.
| distance_threshold | the maximum distance threshold between a point and its nearest neighbor correspondent in order to be considered in the alignment process |
Definition at line 226 of file registration.h.
| void pcl::Registration< PointSource, PointTarget >::setMaximumIterations | ( | int | nr_iterations | ) | [inline] |
Set the maximum number of iterations the internal optimization should run for.
| nr_iterations | the maximum number of iterations the internal optimization should run for |
Definition at line 200 of file registration.h.
| void pcl::Registration< PointSource, PointTarget >::setPointRepresentation | ( | const PointRepresentationConstPtr & | point_representation | ) | [inline] |
Provide a boost shared pointer to the PointRepresentation to be used when comparing points.
| point_representation | the PointRepresentation to be used by the k-D tree |
Definition at line 252 of file registration.h.
| void pcl::Registration< PointSource, PointTarget >::setRadiusSearch | ( | const typename pcl::KdTree< FeatureType >::Ptr & | tree, | |
| float | r, | |||
| std::string | key | |||
| ) | [inline] |
Use radius-search as the search method when finding correspondences for the feature associated with the provided key.
| tree | the KdTree to use to compare features | |
| r | the radius to use when performing the correspondence search | |
| key | a string that uniquely identifies the feature |
Definition at line 274 of file registration.hpp.
| void pcl::Registration< PointSource, PointTarget >::setRANSACOutlierRejectionThreshold | ( | double | inlier_threshold | ) | [inline] |
Set the inlier distance threshold for the internal RANSAC outlier rejection loop.
The method considers a point to be an inlier, if the distance between the target data index and the transformed source index is smaller than the given inlier distance threshold. The value is set by default to 0.05m.
| inlier_threshold | the inlier distance threshold for the internal RANSAC outlier rejection loop |
Definition at line 214 of file registration.h.
| void pcl::Registration< PointSource, PointTarget >::setSourceFeature | ( | const typename pcl::PointCloud< FeatureType >::ConstPtr & | source_feature, | |
| std::string | key | |||
| ) | [inline] |
Provide a pointer to a cloud of feature descriptors associated with the source point cloud.
| source_feature | a cloud of feature descriptors associated with the source point cloud | |
| key | a string that uniquely identifies the feature |
Definition at line 215 of file registration.hpp.
| void pcl::Registration< PointSource, PointTarget >::setTargetFeature | ( | const typename pcl::PointCloud< FeatureType >::ConstPtr & | target_feature, | |
| std::string | key | |||
| ) | [inline] |
Provide a pointer to a cloud of feature descriptors associated with the target point cloud.
| target_feature | a cloud of feature descriptors associated with the target point cloud | |
| key | a string that uniquely identifies the feature |
Definition at line 243 of file registration.hpp.
| void pcl::Registration< PointSource, PointTarget >::setTransformationEpsilon | ( | double | epsilon | ) | [inline] |
Set the transformation epsilon (maximum allowable difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution.
| epsilon | the transformation epsilon in order for an optimization to be considered as having converged to the final solution. |
Definition at line 240 of file registration.h.
bool pcl::Registration< PointSource, PointTarget >::converged_ [protected] |
Holds internal convergence state, given user parameters.
Definition at line 317 of file registration.h.
double pcl::Registration< PointSource, PointTarget >::corr_dist_threshold_ [protected] |
The maximum distance threshold between two correspondent points in source <-> target. If the distance is larger than this threshold, the points will not be ignored in the alignement process.
Definition at line 308 of file registration.h.
FeaturesMap pcl::Registration< PointSource, PointTarget >::features_map_ [private] |
An STL map containing features to use when performing the correspondence search.
Definition at line 371 of file registration.h.
Eigen::Matrix4f pcl::Registration< PointSource, PointTarget >::final_transformation_ [protected] |
The final transformation matrix estimated by the registration method after N iterations.
Definition at line 292 of file registration.h.
double pcl::Registration< PointSource, PointTarget >::inlier_threshold_ [protected] |
The inlier distance threshold for the internal RANSAC outlier rejection loop. The method considers a point to be an inlier, if the distance between the target data index and the transformed source index is smaller than the given inlier distance threshold.
Definition at line 314 of file registration.h.
int pcl::Registration< PointSource, PointTarget >::max_iterations_ [protected] |
The maximum number of iterations the internal optimization should run for.
Definition at line 286 of file registration.h.
int pcl::Registration< PointSource, PointTarget >::min_number_correspondences_ [protected] |
The minimum number of correspondences that the algorithm needs before attempting to estimate the transformation.
Definition at line 322 of file registration.h.
int pcl::Registration< PointSource, PointTarget >::nr_iterations_ [protected] |
The number of iterations the internal optimization ran for (used internally).
Definition at line 283 of file registration.h.
PointRepresentationConstPtr pcl::Registration< PointSource, PointTarget >::point_representation_ [private] |
The number of K nearest neighbors to use for each point.
The point representation used (internal).
Definition at line 368 of file registration.h.
Eigen::Matrix4f pcl::Registration< PointSource, PointTarget >::previous_transformation_ [protected] |
The previous transformation matrix estimated by the registration method (used internally).
Definition at line 298 of file registration.h.
std::string pcl::Registration< PointSource, PointTarget >::reg_name_ [protected] |
The registration method name.
Definition at line 277 of file registration.h.
PointCloudTargetConstPtr pcl::Registration< PointSource, PointTarget >::target_ [protected] |
The input point cloud dataset target.
Definition at line 289 of file registration.h.
Eigen::Matrix4f pcl::Registration< PointSource, PointTarget >::transformation_ [protected] |
The transformation matrix estimated by the registration method.
Definition at line 295 of file registration.h.
double pcl::Registration< PointSource, PointTarget >::transformation_epsilon_ [protected] |
The maximum difference between two consecutive transformations in order to consider convergence (user defined).
Definition at line 303 of file registration.h.
KdTreePtr pcl::Registration< PointSource, PointTarget >::tree_ [protected] |
A pointer to the spatial search object.
Definition at line 280 of file registration.h.
