Registration represents the base registration class. More...

#include <pcl/registration/registration.h>

Inheritance diagram for pcl::Registration< PointSource, PointTarget >:

Collaboration diagram for pcl::Registration< PointSource, PointTarget >:

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.
class	FeatureContainerInterface
Public Types
typedef pcl::KdTree< PointTarget >	KdTree
typedef pcl::KdTree < PointTarget >::Ptr	KdTreePtr
typedef pcl::PointCloud < PointSource >	PointCloudSource
typedef PointCloudSource::Ptr	PointCloudSourcePtr
typedef PointCloudSource::ConstPtr	PointCloudSourceConstPtr
typedef pcl::PointCloud < PointTarget >	PointCloudTarget
typedef PointCloudTarget::Ptr	PointCloudTargetPtr
typedef PointCloudTarget::ConstPtr	PointCloudTargetConstPtr
typedef KdTree::PointRepresentationConstPtr	PointRepresentationConstPtr
typedef std::map< std::string, boost::shared_ptr < FeatureContainerInterface > >	FeaturesMap
Public Member Functions
	Registration ()
	Empty constructor.
virtual	~Registration ()
	destructor.
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).
PointCloudTargetConstPtr const	getInputTarget ()
	Get a pointer to the input point cloud dataset target.
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 >
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 >
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.
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.
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.
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.
Eigen::Matrix4f	getFinalTransformation ()
	Get the final transformation matrix estimated by the registration method.
Eigen::Matrix4f	getLastIncrementalTransformation ()
	Get the last incremental transformation matrix estimated by the registration method.
void	setMaximumIterations (int nr_iterations)
	Set the maximum number of iterations the internal optimization should run for.
int	getMaximumIterations ()
	Get the maximum number of iterations the internal optimization should run for, as set by the user.
void	setRANSACOutlierRejectionThreshold (double inlier_threshold)
	Set the inlier distance threshold for the internal RANSAC outlier rejection loop.
double	getRANSACOutlierRejectionThreshold ()
	Get the inlier distance threshold for the internal outlier rejection loop as set by the user.
void	setMaxCorrespondenceDistance (double distance_threshold)
	Set the maximum distance threshold between two correspondent points in source <-> target.
double	getMaxCorrespondenceDistance ()
	Get the maximum distance threshold between two correspondent points in source <-> target.
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.
double	getTransformationEpsilon ()
	Get the transformation epsilon (maximum allowable difference between two consecutive transformations) as set by the user.
void	setPointRepresentation (const PointRepresentationConstPtr &point_representation)
	Provide a boost shared pointer to the PointRepresentation to be used when comparing points.
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).
bool	hasConverged ()
	Return the state of convergence after the last align run.
void	align (PointCloudSource &output)
	Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output.
void	align (PointCloudSource &output, const Eigen::Matrix4f &guess)
	Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output.
Protected Member Functions
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.
bool	hasValidFeatures ()
	Test that all features are valid (i.e., does each key have a valid source cloud, target cloud, and search method).
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.
Protected Attributes
std::string	reg_name_
	The registration method name.
KdTreePtr	tree_
	A pointer to the spatial search object.
int	nr_iterations_
	The number of iterations the internal optimization ran for (used internally).
int	max_iterations_
	The maximum number of iterations the internal optimization should run for.
PointCloudTargetConstPtr	target_
	The input point cloud dataset target.
Eigen::Matrix4f	final_transformation_
	The final transformation matrix estimated by the registration method after N iterations.
Eigen::Matrix4f	transformation_
	The transformation matrix estimated by the registration method.
Eigen::Matrix4f	previous_transformation_
	The previous transformation matrix estimated by the registration method (used internally).
double	transformation_epsilon_
	The maximum difference between two consecutive transformations in order to consider convergence (user defined).
double	corr_dist_threshold_
	The maximum distance threshold between two correspondent points in source <-> target.
double	inlier_threshold_
	The inlier distance threshold for the internal RANSAC outlier rejection loop.
bool	converged_
	Holds internal convergence state, given user parameters.
int	min_number_correspondences_
	The minimum number of correspondences that the algorithm needs before attempting to estimate the transformation.

Detailed Description

template<typename PointSource, typename PointTarget>
class pcl::Registration< PointSource, PointTarget >

Registration represents the base registration class.

All 3D registration methods should inherit from this class.

Author:: Radu Bogdan Rusu, Michael Dixon

Definition at line 65 of file registration.h.

Member Typedef Documentation

template<typename PointSource, typename PointTarget>

typedef std::map<std::string, boost::shared_ptr<FeatureContainerInterface> > pcl::Registration< PointSource, PointTarget >::FeaturesMap

Definition at line 88 of file registration.h.

template<typename PointSource, typename PointTarget>

typedef pcl::KdTree<PointTarget> pcl::Registration< PointSource, PointTarget >::KdTree

Definition at line 75 of file registration.h.

template<typename PointSource, typename PointTarget>

typedef pcl::KdTree<PointTarget>::Ptr pcl::Registration< PointSource, PointTarget >::KdTreePtr

Definition at line 76 of file registration.h.

template<typename PointSource, typename PointTarget>

typedef pcl::PointCloud<PointSource> pcl::Registration< PointSource, PointTarget >::PointCloudSource

Reimplemented in pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 78 of file registration.h.

template<typename PointSource, typename PointTarget>

typedef PointCloudSource::ConstPtr pcl::Registration< PointSource, PointTarget >::PointCloudSourceConstPtr

Reimplemented in pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 80 of file registration.h.

template<typename PointSource, typename PointTarget>

typedef PointCloudSource::Ptr pcl::Registration< PointSource, PointTarget >::PointCloudSourcePtr

Reimplemented in pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 79 of file registration.h.

template<typename PointSource, typename PointTarget>

typedef pcl::PointCloud<PointTarget> pcl::Registration< PointSource, PointTarget >::PointCloudTarget

Reimplemented in pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 82 of file registration.h.

template<typename PointSource, typename PointTarget>

typedef PointCloudTarget::ConstPtr pcl::Registration< PointSource, PointTarget >::PointCloudTargetConstPtr

Definition at line 84 of file registration.h.

template<typename PointSource, typename PointTarget>

typedef PointCloudTarget::Ptr pcl::Registration< PointSource, PointTarget >::PointCloudTargetPtr

Definition at line 83 of file registration.h.

template<typename PointSource, typename PointTarget>

typedef KdTree::PointRepresentationConstPtr pcl::Registration< PointSource, PointTarget >::PointRepresentationConstPtr

Definition at line 86 of file registration.h.

Constructor & Destructor Documentation

template<typename PointSource, typename PointTarget>

pcl::Registration< PointSource, PointTarget >::Registration ( ) [inline]

Empty constructor.

Definition at line 91 of file registration.h.

template<typename PointSource, typename PointTarget>

virtual pcl::Registration< PointSource, PointTarget >::~Registration ( ) [inline, virtual]

destructor.

Definition at line 103 of file registration.h.

Member Function Documentation

template<typename PointSource , typename PointTarget >

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.

Parameters:

output

the resultant input transfomed point cloud dataset

Definition at line 243 of file registration.hpp.

template<typename PointSource , typename PointTarget >

void pcl::Registration< PointSource, PointTarget >::align	(	PointCloudSource &	output,
		const Eigen::Matrix4f &	guess
	)			`[inline]`

Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output.

Parameters:

	output	the resultant input transfomed point cloud dataset
	guess	the initial gross estimation of the transformation

Definition at line 295 of file registration.hpp.

template<typename PointSource , typename 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.

Parameters:

	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 164 of file registration.hpp.

template<typename PointSource, typename PointTarget>

const std::string& pcl::Registration< PointSource, PointTarget >::getClassName ( ) const [inline, protected]

Abstract class get name method.

Definition at line 335 of file registration.h.

template<typename PointSource, typename PointTarget>

Eigen::Matrix4f pcl::Registration< PointSource, PointTarget >::getFinalTransformation ( ) [inline]

Get the final transformation matrix estimated by the registration method.

Definition at line 161 of file registration.h.

template<typename PointSource , typename PointTarget >

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).

Parameters:

max_range

maximum allowable distance between a point and its correspondent neighbor in the target (default: double::max)

Definition at line 202 of file registration.hpp.

template<typename PointSource, typename PointTarget>

PointCloudTargetConstPtr const pcl::Registration< PointSource, PointTarget >::getInputTarget ( ) [inline]

Get a pointer to the input point cloud dataset target.

Definition at line 113 of file registration.h.

template<typename PointSource, typename PointTarget>

Eigen::Matrix4f pcl::Registration< PointSource, PointTarget >::getLastIncrementalTransformation ( ) [inline]

Get the last incremental transformation matrix estimated by the registration method.

Definition at line 165 of file registration.h.

template<typename PointSource, typename PointTarget>

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 203 of file registration.h.

template<typename PointSource, typename PointTarget>

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 175 of file registration.h.

template<typename PointSource, typename PointTarget>

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 189 of file registration.h.

template<typename PointSource , typename PointTarget >

template<typename FeatureType >

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.

Parameters:

key

a string that uniquely identifies the feature (must match the key provided by setSourceFeature)

Definition at line 74 of file registration.hpp.

template<typename PointSource , typename PointTarget >

template<typename FeatureType >

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.

Parameters:

key

a string that uniquely identifies the feature (must match the key provided by setTargetFeature)

Definition at line 102 of file registration.hpp.

template<typename PointSource, typename PointTarget>

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 217 of file registration.h.

template<typename PointSource, typename PointTarget>

bool pcl::Registration< PointSource, PointTarget >::hasConverged ( ) [inline]

Return the state of convergence after the last align run.

Definition at line 237 of file registration.h.

template<typename PointSource , typename PointTarget >

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 145 of file registration.hpp.

template<typename PointSource, typename PointTarget>

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.

Parameters:

	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 310 of file registration.h.

template<typename PointSource , typename PointTarget >

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).

Parameters:

cloud

the input point cloud target

Definition at line 41 of file registration.hpp.

template<typename PointSource , typename PointTarget >

template<typename FeatureType >

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.

Parameters:

	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 133 of file registration.hpp.

template<typename PointSource, typename PointTarget>

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.

Parameters:

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 197 of file registration.h.

template<typename PointSource, typename PointTarget>

void pcl::Registration< PointSource, PointTarget >::setMaximumIterations ( int nr_iterations ) [inline]

Set the maximum number of iterations the internal optimization should run for.

Parameters:

nr_iterations

the maximum number of iterations the internal optimization should run for

Definition at line 171 of file registration.h.

template<typename PointSource, typename PointTarget>

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.

Parameters:

point_representation

the PointRepresentation to be used by the k-D tree

Definition at line 223 of file registration.h.

template<typename PointSource , typename PointTarget >

template<typename FeatureType >

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.

Parameters:

	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 120 of file registration.hpp.

template<typename PointSource, typename PointTarget>

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.

Parameters:

inlier_threshold

the inlier distance threshold for the internal RANSAC outlier rejection loop

Definition at line 185 of file registration.h.

template<typename PointSource , typename PointTarget >

template<typename FeatureType >

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.

Parameters:

	source_feature	a cloud of feature descriptors associated with the source point cloud
	key	a string that uniquely identifies the feature

Definition at line 61 of file registration.hpp.

template<typename PointSource , typename PointTarget >

template<typename FeatureType >

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.

Parameters:

	target_feature	a cloud of feature descriptors associated with the target point cloud
	key	a string that uniquely identifies the feature

Definition at line 89 of file registration.hpp.

template<typename PointSource, typename PointTarget>

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.

Parameters:

epsilon

the transformation epsilon in order for an optimization to be considered as having converged to the final solution.

Definition at line 211 of file registration.h.

Member Data Documentation

template<typename PointSource, typename PointTarget>

bool pcl::Registration< PointSource, PointTarget >::converged_ [protected]

Holds internal convergence state, given user parameters.

Definition at line 296 of file registration.h.

template<typename PointSource, typename PointTarget>

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 287 of file registration.h.

template<typename PointSource, typename PointTarget>

Eigen::Matrix4f pcl::Registration< PointSource, PointTarget >::final_transformation_ [protected]

The final transformation matrix estimated by the registration method after N iterations.

Definition at line 271 of file registration.h.

template<typename PointSource, typename PointTarget>

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 293 of file registration.h.

template<typename PointSource, typename PointTarget>

int pcl::Registration< PointSource, PointTarget >::max_iterations_ [protected]

The maximum number of iterations the internal optimization should run for.

Definition at line 265 of file registration.h.

template<typename PointSource, typename PointTarget>

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 301 of file registration.h.

template<typename PointSource, typename PointTarget>

int pcl::Registration< PointSource, PointTarget >::nr_iterations_ [protected]

The number of iterations the internal optimization ran for (used internally).

Definition at line 262 of file registration.h.

template<typename PointSource, typename PointTarget>

Eigen::Matrix4f pcl::Registration< PointSource, PointTarget >::previous_transformation_ [protected]

The previous transformation matrix estimated by the registration method (used internally).

Definition at line 277 of file registration.h.

template<typename PointSource, typename PointTarget>

std::string pcl::Registration< PointSource, PointTarget >::reg_name_ [protected]

The registration method name.

Definition at line 256 of file registration.h.

template<typename PointSource, typename PointTarget>

PointCloudTargetConstPtr pcl::Registration< PointSource, PointTarget >::target_ [protected]

The input point cloud dataset target.

Definition at line 268 of file registration.h.

template<typename PointSource, typename PointTarget>

Eigen::Matrix4f pcl::Registration< PointSource, PointTarget >::transformation_ [protected]

The transformation matrix estimated by the registration method.

Definition at line 274 of file registration.h.

template<typename PointSource, typename PointTarget>

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 282 of file registration.h.

template<typename PointSource, typename PointTarget>

KdTreePtr pcl::Registration< PointSource, PointTarget >::tree_ [protected]

A pointer to the spatial search object.

Definition at line 259 of file registration.h.

The documentation for this class was generated from the following files:

/tmp/pcl-1.0.1/registration/include/pcl/registration/registration.h
/tmp/pcl-1.0.1/registration/include/pcl/registration/impl/registration.hpp

pcl::Registration< PointSource, PointTarget > Class Template Reference [Module registration]

Classes

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

template<typename PointSource, typename PointTarget> class pcl::Registration< PointSource, PointTarget >

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

pcl::Registration< PointSource, PointTarget > Class Template Reference
[Module registration]

template<typename PointSource, typename PointTarget>
class pcl::Registration< PointSource, PointTarget >