W3cubDocs

Registration represents the base registration class for general purpose, ICP-like methods. More...

#include <pcl/registration/registration.h>

Public Types
using	Matrix4 = Eigen::Matrix< Scalar, 4, 4 >

using	Ptr = shared_ptr< Registration< PointSource, PointTarget, Scalar > >

using	ConstPtr = shared_ptr< const Registration< PointSource, PointTarget, Scalar > >

using	CorrespondenceRejectorPtr = pcl::registration::CorrespondenceRejector::Ptr

using	KdTree = pcl::search::KdTree< PointTarget >

using	KdTreePtr = typename KdTree::Ptr

using	KdTreeReciprocal = pcl::search::KdTree< PointSource >

using	KdTreeReciprocalPtr = typename KdTreeReciprocal::Ptr

using	PointCloudSource = pcl::PointCloud< PointSource >

using	PointCloudSourcePtr = typename PointCloudSource::Ptr

using	PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr

using	PointCloudTarget = pcl::PointCloud< PointTarget >

using	PointCloudTargetPtr = typename PointCloudTarget::Ptr

using	PointCloudTargetConstPtr = typename PointCloudTarget::ConstPtr

using	PointRepresentationConstPtr = typename KdTree::PointRepresentationConstPtr

using	TransformationEstimation = typename pcl::registration::TransformationEstimation< PointSource, PointTarget, Scalar >

using	TransformationEstimationPtr = typename TransformationEstimation::Ptr

using	TransformationEstimationConstPtr = typename TransformationEstimation::ConstPtr

using	CorrespondenceEstimation = pcl::registration::CorrespondenceEstimationBase< PointSource, PointTarget, Scalar >

using	CorrespondenceEstimationPtr = typename CorrespondenceEstimation::Ptr

using	CorrespondenceEstimationConstPtr = typename CorrespondenceEstimation::ConstPtr

using	UpdateVisualizerCallbackSignature = void(const pcl::PointCloud< PointSource > &, const pcl::Indices &, const pcl::PointCloud< PointTarget > &, const pcl::Indices &)
	The callback signature to the function updating intermediate source point cloud position during it's registration to the target point cloud. More...

Public Types inherited from pcl::PCLBase< PointSource >
using	PointCloud = pcl::PointCloud< PointSource >

using	PointCloudPtr = typename PointCloud::Ptr

using	PointCloudConstPtr = typename PointCloud::ConstPtr

using	PointIndicesPtr = PointIndices::Ptr

using	PointIndicesConstPtr = PointIndices::ConstPtr

Public Member Functions
	Registration ()
	Empty constructor. More...

	~Registration ()
	destructor. More...

void	setTransformationEstimation (const TransformationEstimationPtr &te)
	Provide a pointer to the transformation estimation object. More...

void	setCorrespondenceEstimation (const CorrespondenceEstimationPtr &ce)
	Provide a pointer to the correspondence estimation object. More...

virtual void	setInputSource (const PointCloudSourceConstPtr &cloud)
	Provide a pointer to the input source (e.g., the point cloud that we want to align to the target) More...

const PointCloudSourceConstPtr	getInputSource ()
	Get a pointer to the input point cloud dataset target. More...

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) More...

const PointCloudTargetConstPtr	getInputTarget ()
	Get a pointer to the input point cloud dataset target. More...

void	setSearchMethodTarget (const KdTreePtr &tree, bool force_no_recompute=false)
	Provide a pointer to the search object used to find correspondences in the target cloud. More...

KdTreePtr	getSearchMethodTarget () const
	Get a pointer to the search method used to find correspondences in the target cloud. More...

void	setSearchMethodSource (const KdTreeReciprocalPtr &tree, bool force_no_recompute=false)
	Provide a pointer to the search object used to find correspondences in the source cloud (usually used by reciprocal correspondence finding). More...

KdTreeReciprocalPtr	getSearchMethodSource () const
	Get a pointer to the search method used to find correspondences in the source cloud. More...

Matrix4	getFinalTransformation ()
	Get the final transformation matrix estimated by the registration method. More...

Matrix4	getLastIncrementalTransformation ()
	Get the last incremental transformation matrix estimated by the registration method. More...

void	setMaximumIterations (int nr_iterations)
	Set the maximum number of iterations the internal optimization should run for. More...

int	getMaximumIterations ()
	Get the maximum number of iterations the internal optimization should run for, as set by the user. More...

void	setRANSACIterations (int ransac_iterations)
	Set the number of iterations RANSAC should run for. More...

double	getRANSACIterations ()
	Get the number of iterations RANSAC should run for, as set by the user. More...

void	setRANSACOutlierRejectionThreshold (double inlier_threshold)
	Set the inlier distance threshold for the internal RANSAC outlier rejection loop. More...

double	getRANSACOutlierRejectionThreshold ()
	Get the inlier distance threshold for the internal outlier rejection loop as set by the user. More...

void	setMaxCorrespondenceDistance (double distance_threshold)
	Set the maximum distance threshold between two correspondent points in source <-> target. More...

double	getMaxCorrespondenceDistance ()
	Get the maximum distance threshold between two correspondent points in source <-> target. More...

void	setTransformationEpsilon (double epsilon)
	Set the transformation epsilon (maximum allowable translation squared difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution. More...

double	getTransformationEpsilon ()
	Get the transformation epsilon (maximum allowable translation squared difference between two consecutive transformations) as set by the user. More...

void	setTransformationRotationEpsilon (double epsilon)
	Set the transformation rotation epsilon (maximum allowable rotation difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution. More...

double	getTransformationRotationEpsilon ()
	Get the transformation rotation epsilon (maximum allowable difference between two consecutive transformations) as set by the user (epsilon is the cos(angle) in a axis-angle representation). More...

void	setEuclideanFitnessEpsilon (double epsilon)
	Set the maximum allowed Euclidean error between two consecutive steps in the ICP loop, before the algorithm is considered to have converged. More...

double	getEuclideanFitnessEpsilon ()
	Get the maximum allowed distance error before the algorithm will be considered to have converged, as set by the user. More...

void	setPointRepresentation (const PointRepresentationConstPtr &point_representation)
	Provide a boost shared pointer to the PointRepresentation to be used when comparing points. More...

bool	registerVisualizationCallback (std::function< UpdateVisualizerCallbackSignature > &visualizerCallback)
	Register the user callback function which will be called from registration thread in order to update point cloud obtained after each iteration. More...

double	getFitnessScore (double max_range=std::numeric_limits< double >::max())
	Obtain the Euclidean fitness score (e.g., mean of squared distances from the source to the target) More...

double	getFitnessScore (const std::vector< float > &distances_a, const std::vector< float > &distances_b)
	Obtain the Euclidean fitness score (e.g., mean of squared distances from the source to the target) from two sets of correspondence distances (distances between source and target points) More...

bool	hasConverged () const
	Return the state of convergence after the last align run. More...

void	align (PointCloudSource &output)
	Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output. More...

void	align (PointCloudSource &output, const Matrix4 &guess)
	Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output. More...

const std::string &	getClassName () const
	Abstract class get name method. More...

bool	initCompute ()
	Internal computation initialization. More...

bool	initComputeReciprocal ()
	Internal computation when reciprocal lookup is needed. More...

void	addCorrespondenceRejector (const CorrespondenceRejectorPtr &rejector)
	Add a new correspondence rejector to the list. More...

std::vector< CorrespondenceRejectorPtr >	getCorrespondenceRejectors ()
	Get the list of correspondence rejectors. More...

bool	removeCorrespondenceRejector (unsigned int i)
	Remove the i-th correspondence rejector in the list. More...

void	clearCorrespondenceRejectors ()
	Clear the list of correspondence rejectors. More...

Public Member Functions inherited from pcl::PCLBase< PointSource >
	PCLBase ()
	Empty constructor. More...

	PCLBase (const PCLBase &base)
	Copy constructor. More...

virtual	~PCLBase ()=default
	Destructor. More...

virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset. More...

const PointCloudConstPtr	getInputCloud () const
	Get a pointer to the input point cloud dataset. More...

virtual void	setIndices (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...

virtual void	setIndices (const IndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...

virtual void	setIndices (const PointIndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...

virtual void	setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols)
	Set the indices for the points laying within an interest region of the point cloud. More...

IndicesPtr	getIndices ()
	Get a pointer to the vector of indices used. More...

const IndicesConstPtr	getIndices () const
	Get a pointer to the vector of indices used. More...

const PointSource &	operator[] (std::size_t pos) const
	Override PointCloud operator[] to shorten code. More...

Protected Member Functions
bool	searchForNeighbors (const PointCloudSource &cloud, int index, pcl::Indices &indices, std::vector< float > &distances)
	Search for the closest nearest neighbor of a given point. More...

virtual void	computeTransformation (PointCloudSource &output, const Matrix4 &guess)=0
	Abstract transformation computation method with initial guess. More...

Protected Member Functions inherited from pcl::PCLBase< PointSource >
bool	initCompute ()
	This method should get called before starting the actual computation. More...

bool	deinitCompute ()
	This method should get called after finishing the actual computation. More...

Protected Attributes
std::string	reg_name_
	The registration method name. More...

KdTreePtr	tree_
	A pointer to the spatial search object. More...

KdTreeReciprocalPtr	tree_reciprocal_
	A pointer to the spatial search object of the source. More...

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

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

int	ransac_iterations_
	The number of iterations RANSAC should run for. More...

PointCloudTargetConstPtr	target_
	The input point cloud dataset target. More...

Matrix4	final_transformation_
	The final transformation matrix estimated by the registration method after N iterations. More...

Matrix4	transformation_
	The transformation matrix estimated by the registration method. More...

Matrix4	previous_transformation_
	The previous transformation matrix estimated by the registration method (used internally). More...

double	transformation_epsilon_
	The maximum difference between two consecutive transformations in order to consider convergence (user defined). More...

double	transformation_rotation_epsilon_
	The maximum rotation difference between two consecutive transformations in order to consider convergence (user defined). More...

double	euclidean_fitness_epsilon_
	The maximum allowed Euclidean error between two consecutive steps in the ICP loop, before the algorithm is considered to have converged. More...

double	corr_dist_threshold_
	The maximum distance threshold between two correspondent points in source <-> target. More...

double	inlier_threshold_
	The inlier distance threshold for the internal RANSAC outlier rejection loop. More...

bool	converged_
	Holds internal convergence state, given user parameters. More...

int	min_number_correspondences_
	The minimum number of correspondences that the algorithm needs before attempting to estimate the transformation. More...

CorrespondencesPtr	correspondences_
	The set of correspondences determined at this ICP step. More...

TransformationEstimationPtr	transformation_estimation_
	A TransformationEstimation object, used to calculate the 4x4 rigid transformation. More...

CorrespondenceEstimationPtr	correspondence_estimation_
	A CorrespondenceEstimation object, used to estimate correspondences between the source and the target cloud. More...

std::vector< CorrespondenceRejectorPtr >	correspondence_rejectors_
	The list of correspondence rejectors to use. More...

bool	target_cloud_updated_
	Variable that stores whether we have a new target cloud, meaning we need to pre-process it again. More...

bool	source_cloud_updated_
	Variable that stores whether we have a new source cloud, meaning we need to pre-process it again. More...

bool	force_no_recompute_
	A flag which, if set, means the tree operating on the target cloud will never be recomputed. More...

bool	force_no_recompute_reciprocal_
	A flag which, if set, means the tree operating on the source cloud will never be recomputed. More...

std::function< UpdateVisualizerCallbackSignature >	update_visualizer_
	Callback function to update intermediate source point cloud position during it's registration to the target point cloud. More...

Protected Attributes inherited from pcl::PCLBase< PointSource >
PointCloudConstPtr	input_
	The input point cloud dataset. More...

IndicesPtr	indices_
	A pointer to the vector of point indices to use. More...

bool	use_indices_
	Set to true if point indices are used. More...

bool	fake_indices_
	If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More...

Detailed Description

template<typename PointSource, typename PointTarget, typename Scalar = float>
class pcl::Registration< PointSource, PointTarget, Scalar >

Registration represents the base registration class for general purpose, ICP-like methods.

Author: Radu B. Rusu, Michael Dixon

Definition at line 57 of file registration.h.

Member Typedef Documentation

ConstPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::ConstPtr = shared_ptr<const Registration<PointSource, PointTarget, Scalar> >

Definition at line 67 of file registration.h.

CorrespondenceEstimation

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::CorrespondenceEstimation = pcl::registration::CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>

Definition at line 92 of file registration.h.

CorrespondenceEstimationConstPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::CorrespondenceEstimationConstPtr = typename CorrespondenceEstimation::ConstPtr

Definition at line 94 of file registration.h.

CorrespondenceEstimationPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::CorrespondenceEstimationPtr = typename CorrespondenceEstimation::Ptr

Definition at line 93 of file registration.h.

CorrespondenceRejectorPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::CorrespondenceRejectorPtr = pcl::registration::CorrespondenceRejector::Ptr

Definition at line 69 of file registration.h.

KdTree

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::KdTree = pcl::search::KdTree<PointTarget>

Definition at line 70 of file registration.h.

KdTreePtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::KdTreePtr = typename KdTree::Ptr

Definition at line 71 of file registration.h.

KdTreeReciprocal

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::KdTreeReciprocal = pcl::search::KdTree<PointSource>

Definition at line 73 of file registration.h.

KdTreeReciprocalPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::KdTreeReciprocalPtr = typename KdTreeReciprocal::Ptr

Definition at line 74 of file registration.h.

Matrix4

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::Matrix4 = Eigen::Matrix<Scalar, 4, 4>

Definition at line 59 of file registration.h.

PointCloudSource

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::PointCloudSource = pcl::PointCloud<PointSource>

Definition at line 76 of file registration.h.

PointCloudSourceConstPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr

Definition at line 78 of file registration.h.

PointCloudSourcePtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::PointCloudSourcePtr = typename PointCloudSource::Ptr

Definition at line 77 of file registration.h.

PointCloudTarget

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::PointCloudTarget = pcl::PointCloud<PointTarget>

Definition at line 80 of file registration.h.

PointCloudTargetConstPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::PointCloudTargetConstPtr = typename PointCloudTarget::ConstPtr

Definition at line 82 of file registration.h.

PointCloudTargetPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::PointCloudTargetPtr = typename PointCloudTarget::Ptr

Definition at line 81 of file registration.h.

PointRepresentationConstPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::PointRepresentationConstPtr = typename KdTree::PointRepresentationConstPtr

Definition at line 84 of file registration.h.

Ptr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::Ptr = shared_ptr<Registration<PointSource, PointTarget, Scalar> >

Definition at line 66 of file registration.h.

TransformationEstimation

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::TransformationEstimation = typename pcl::registration:: TransformationEstimation<PointSource, PointTarget, Scalar>

Definition at line 87 of file registration.h.

TransformationEstimationConstPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::TransformationEstimationConstPtr = typename TransformationEstimation::ConstPtr

Definition at line 89 of file registration.h.

TransformationEstimationPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::TransformationEstimationPtr = typename TransformationEstimation::Ptr

Definition at line 88 of file registration.h.

UpdateVisualizerCallbackSignature

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::Registration< PointSource, PointTarget, Scalar >::UpdateVisualizerCallbackSignature = void(const pcl::PointCloud<PointSource>&, const pcl::Indices&, const pcl::PointCloud<PointTarget>&, const pcl::Indices&)

The callback signature to the function updating intermediate source point cloud position during it's registration to the target point cloud.

Parameters

[in]	cloud_src	- the point cloud which will be updated to match target
[in]	indices_src	- a selector of points in cloud_src
[in]	cloud_tgt	- the point cloud we want to register against
[in]	indices_tgt	- a selector of points in cloud_tgt

Definition at line 106 of file registration.h.

Constructor & Destructor Documentation

Registration()

template<typename PointSource , typename PointTarget , typename Scalar = float>

pcl::Registration< PointSource, PointTarget, Scalar >::Registration ( )

inline

Empty constructor.

Definition at line 109 of file registration.h.

~Registration()

template<typename PointSource , typename PointTarget , typename Scalar = float>

pcl::Registration< PointSource, PointTarget, Scalar >::~Registration ( )

inline

destructor.

Definition at line 137 of file registration.h.

Member Function Documentation

addCorrespondenceRejector()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::addCorrespondenceRejector ( const CorrespondenceRejectorPtr & rejector )

inline

Add a new correspondence rejector to the list.

Parameters

[in] rejector the new correspondence rejector to concatenate

Code example:

CorrespondenceRejectorDistance rej;
rej.setInputCloud<PointXYZ> (keypoints_src);
rej.setInputTarget<PointXYZ> (keypoints_tgt);
rej.setMaximumDistance (1);
rej.setInputCorrespondences (all_correspondences);
 
// or...

Definition at line 525 of file registration.h.

align() [1/2]

template<typename PointSource , typename PointTarget , typename Scalar >

void pcl::Registration< PointSource, PointTarget, Scalar >::align ( PointCloudSource & output )

inline

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

Parameters

[out] output the resultant input transformed point cloud dataset

Definition at line 166 of file registration.hpp.

align() [2/2]

template<typename PointSource , typename PointTarget , typename Scalar >

void pcl::Registration< PointSource, PointTarget, Scalar >::align	(	PointCloudSource &	output,
		const Matrix4 &	guess
	)

inline

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

Parameters

[out]	output	the resultant input transformed point cloud dataset
[in]	guess	the initial gross estimation of the transformation

Definition at line 173 of file registration.hpp.

clearCorrespondenceRejectors()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::clearCorrespondenceRejectors ( )

inline

Clear the list of correspondence rejectors.

Definition at line 551 of file registration.h.

computeTransformation()

template<typename PointSource , typename PointTarget , typename Scalar = float>

virtual void pcl::Registration< PointSource, PointTarget, Scalar >::computeTransformation	(	PointCloudSource &	output,
		const Matrix4 &	guess
	)

protectedpure virtual

Abstract transformation computation method with initial guess.

getClassName()

template<typename PointSource , typename PointTarget , typename Scalar = float>

const std::string& pcl::Registration< PointSource, PointTarget, Scalar >::getClassName ( ) const

inline

Abstract class get name method.

Definition at line 495 of file registration.h.

Referenced by pcl::RegistrationVisualizer< PointSource, PointTarget >::setRegistration().

getCorrespondenceRejectors()

template<typename PointSource , typename PointTarget , typename Scalar = float>

std::vector<CorrespondenceRejectorPtr> pcl::Registration< PointSource, PointTarget, Scalar >::getCorrespondenceRejectors ( )

inline

Get the list of correspondence rejectors.

Definition at line 532 of file registration.h.

getEuclideanFitnessEpsilon()

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::getEuclideanFitnessEpsilon ( )

inline

Get the maximum allowed distance error before the algorithm will be considered to have converged, as set by the user.

See setEuclideanFitnessEpsilon

Definition at line 424 of file registration.h.

getFinalTransformation()

template<typename PointSource , typename PointTarget , typename Scalar = float>

Matrix4 pcl::Registration< PointSource, PointTarget, Scalar >::getFinalTransformation ( )

inline

Get the final transformation matrix estimated by the registration method.

Definition at line 271 of file registration.h.

getFitnessScore() [1/2]

template<typename PointSource , typename PointTarget , typename Scalar >

double pcl::Registration< PointSource, PointTarget, Scalar >::getFitnessScore	(	const std::vector< float > &	distances_a,
		const std::vector< float > &	distances_b
	)

inline

Obtain the Euclidean fitness score (e.g., mean of squared distances from the source to the target) from two sets of correspondence distances (distances between source and target points)

Parameters

[in]	distances_a	the first set of distances between correspondences
[in]	distances_b	the second set of distances between correspondences

Definition at line 122 of file registration.hpp.

getFitnessScore() [2/2]

template<typename PointSource , typename PointTarget , typename Scalar >

double pcl::Registration< PointSource, PointTarget, Scalar >::getFitnessScore ( double max_range = std::numeric_limits<double>::max() )

inline

Obtain the Euclidean fitness score (e.g., mean of squared distances from the source to the target)

Parameters

[in] max_range maximum allowable distance between a point and its correspondence in the target (default: double::max)

Definition at line 134 of file registration.hpp.

getInputSource()

template<typename PointSource , typename PointTarget , typename Scalar = float>

const PointCloudSourceConstPtr pcl::Registration< PointSource, PointTarget, Scalar >::getInputSource ( )

inline

Get a pointer to the input point cloud dataset target.

Definition at line 201 of file registration.h.

getInputTarget()

template<typename PointSource , typename PointTarget , typename Scalar = float>

const PointCloudTargetConstPtr pcl::Registration< PointSource, PointTarget, Scalar >::getInputTarget ( )

inline

Get a pointer to the input point cloud dataset target.

Definition at line 214 of file registration.h.

getLastIncrementalTransformation()

template<typename PointSource , typename PointTarget , typename Scalar = float>

Matrix4 pcl::Registration< PointSource, PointTarget, Scalar >::getLastIncrementalTransformation ( )

inline

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

Definition at line 279 of file registration.h.

getMaxCorrespondenceDistance()

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::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 358 of file registration.h.

getMaximumIterations()

template<typename PointSource , typename PointTarget , typename Scalar = float>

int pcl::Registration< PointSource, PointTarget, Scalar >::getMaximumIterations ( )

inline

Get the maximum number of iterations the internal optimization should run for, as set by the user.

Definition at line 297 of file registration.h.

getRANSACIterations()

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::getRANSACIterations ( )

inline

Get the number of iterations RANSAC should run for, as set by the user.

Definition at line 313 of file registration.h.

getRANSACOutlierRejectionThreshold()

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::getRANSACOutlierRejectionThreshold ( )

inline

Get the inlier distance threshold for the internal outlier rejection loop as set by the user.

Definition at line 336 of file registration.h.

getSearchMethodSource()

template<typename PointSource , typename PointTarget , typename Scalar = float>

KdTreeReciprocalPtr pcl::Registration< PointSource, PointTarget, Scalar >::getSearchMethodSource ( ) const

inline

Get a pointer to the search method used to find correspondences in the source cloud.

Definition at line 263 of file registration.h.

getSearchMethodTarget()

template<typename PointSource , typename PointTarget , typename Scalar = float>

KdTreePtr pcl::Registration< PointSource, PointTarget, Scalar >::getSearchMethodTarget ( ) const

inline

Get a pointer to the search method used to find correspondences in the target cloud.

Definition at line 238 of file registration.h.

getTransformationEpsilon()

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::getTransformationEpsilon ( )

inline

Get the transformation epsilon (maximum allowable translation squared difference between two consecutive transformations) as set by the user.

Definition at line 379 of file registration.h.

getTransformationRotationEpsilon()

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::getTransformationRotationEpsilon ( )

inline

Get the transformation rotation epsilon (maximum allowable difference between two consecutive transformations) as set by the user (epsilon is the cos(angle) in a axis-angle representation).

Definition at line 402 of file registration.h.

hasConverged()

template<typename PointSource , typename PointTarget , typename Scalar = float>

bool pcl::Registration< PointSource, PointTarget, Scalar >::hasConverged ( ) const

inline

Return the state of convergence after the last align run.

Definition at line 473 of file registration.h.

initCompute()

template<typename PointSource , typename PointTarget , typename Scalar >

bool pcl::Registration< PointSource, PointTarget, Scalar >::initCompute

Internal computation initialization.

Definition at line 75 of file registration.hpp.

initComputeReciprocal()

template<typename PointSource , typename PointTarget , typename Scalar >

bool pcl::Registration< PointSource, PointTarget, Scalar >::initComputeReciprocal

Internal computation when reciprocal lookup is needed.

Definition at line 105 of file registration.hpp.

registerVisualizationCallback()

template<typename PointSource , typename PointTarget , typename Scalar = float>

bool pcl::Registration< PointSource, PointTarget, Scalar >::registerVisualizationCallback ( std::function< UpdateVisualizerCallbackSignature > & visualizerCallback )

inline

Register the user callback function which will be called from registration thread in order to update point cloud obtained after each iteration.

Parameters

[in] visualizerCallback reference of the user callback function

Definition at line 444 of file registration.h.

Referenced by pcl::RegistrationVisualizer< PointSource, PointTarget >::setRegistration().

removeCorrespondenceRejector()

template<typename PointSource , typename PointTarget , typename Scalar = float>

bool pcl::Registration< PointSource, PointTarget, Scalar >::removeCorrespondenceRejector ( unsigned int i )

inline

Remove the i-th correspondence rejector in the list.

Parameters

[in] i the position of the correspondence rejector in the list to remove

Definition at line 541 of file registration.h.

searchForNeighbors()

template<typename PointSource , typename PointTarget , typename Scalar = float>

bool pcl::Registration< PointSource, PointTarget, Scalar >::searchForNeighbors	(	const PointCloudSource &	cloud,
		int	index,
		pcl::Indices &	indices,
		std::vector< float > &	distances
	)

inlineprotected

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 673 of file registration.h.

setCorrespondenceEstimation()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::setCorrespondenceEstimation ( const CorrespondenceEstimationPtr & ce )

inline

Provide a pointer to the correspondence estimation object.

(e.g., regular, reciprocal, normal shooting etc.)

Parameters

[in] ce is the pointer to the corresponding correspondence estimation object

Code example:

CorrespondenceEstimation<PointXYZ, PointXYZ>::Ptr
 ce (new CorrespondenceEstimation<PointXYZ, PointXYZ>);
ce->setInputSource (source);
ce->setInputTarget (target);
icp.setCorrespondenceEstimation (ce);
// or...
CorrespondenceEstimationNormalShooting<PointNormal, PointNormal, PointNormal>::Ptr
 cens (new CorrespondenceEstimationNormalShooting<PointNormal, PointNormal>);
ce->setInputSource (source);
ce->setInputTarget (target);
ce->setSourceNormals (source);
ce->setTargetNormals (target);
icp.setCorrespondenceEstimation (cens);

Definition at line 186 of file registration.h.

setEuclideanFitnessEpsilon()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::setEuclideanFitnessEpsilon ( double epsilon )

inline

Set the maximum allowed Euclidean error between two consecutive steps in the ICP loop, before the algorithm is considered to have converged.

The error is estimated as the sum of the differences between correspondences in an Euclidean sense, divided by the number of correspondences.

Parameters

[in] epsilon the maximum allowed distance error before the algorithm will be considered to have converged

Definition at line 414 of file registration.h.

setInputSource()

template<typename PointSource , typename PointTarget , typename Scalar >

void pcl::Registration< PointSource, PointTarget, Scalar >::setInputSource ( const PointCloudSourceConstPtr & cloud )

inlinevirtual

Provide a pointer to the input source (e.g., the point cloud that we want to align to the target)

Parameters

[in] cloud the input point cloud source

Reimplemented in pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >, pcl::IterativeClosestPoint< PointSource, PointTarget, float >, pcl::IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >, pcl::IterativeClosestPoint< PointSource, PointTarget >, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >, pcl::GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >, pcl::GeneralizedIterativeClosestPoint6D, and pcl::JointIterativeClosestPoint< PointSource, PointTarget, Scalar >.

Definition at line 47 of file registration.hpp.

Referenced by pcl::IterativeClosestPoint< PointSource, PointTarget >::setInputSource().

setInputTarget()

template<typename PointSource , typename PointTarget , typename Scalar >

void pcl::Registration< PointSource, PointTarget, Scalar >::setInputTarget ( const PointCloudTargetConstPtr & cloud )

inlinevirtual

Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to)

Parameters

[in] cloud the input point cloud target

Reimplemented in pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >, pcl::GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >, pcl::GeneralizedIterativeClosestPoint6D, pcl::PPFRegistration< PointSource, PointTarget >, pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >, pcl::IterativeClosestPoint< PointSource, PointTarget, float >, pcl::IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >, pcl::IterativeClosestPoint< PointSource, PointTarget >, pcl::NormalDistributionsTransform< PointSource, PointTarget >, and pcl::JointIterativeClosestPoint< PointSource, PointTarget, Scalar >.

Definition at line 61 of file registration.hpp.

Referenced by pcl::NormalDistributionsTransform< PointSource, PointTarget >::setInputTarget(), and pcl::IterativeClosestPoint< PointSource, PointTarget >::setInputTarget().

setMaxCorrespondenceDistance()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::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

[in] 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 348 of file registration.h.

setMaximumIterations()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::setMaximumIterations ( int nr_iterations )

inline

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

Parameters

[in] nr_iterations the maximum number of iterations the internal optimization should run for

Definition at line 289 of file registration.h.

setPointRepresentation()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::setPointRepresentation ( const PointRepresentationConstPtr & point_representation )

inline

Provide a boost shared pointer to the PointRepresentation to be used when comparing points.

Parameters

[in] point_representation the PointRepresentation to be used by the k-D tree

Definition at line 434 of file registration.h.

setRANSACIterations()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::setRANSACIterations ( int ransac_iterations )

inline

Set the number of iterations RANSAC should run for.

Parameters

[in] ransac_iterations is the number of iterations RANSAC should run for

Definition at line 306 of file registration.h.

setRANSACOutlierRejectionThreshold()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::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

[in] inlier_threshold the inlier distance threshold for the internal RANSAC outlier rejection loop

Definition at line 328 of file registration.h.

setSearchMethodSource()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::setSearchMethodSource	(	const KdTreeReciprocalPtr &	tree,
		bool	force_no_recompute = `false`
	)

inline

Provide a pointer to the search object used to find correspondences in the source cloud (usually used by reciprocal correspondence finding).

Parameters

[in]	tree	a pointer to the spatial search object.
[in]	force_no_recompute	If set to true, this tree will NEVER be recomputed, regardless of calls to setInputSource. Only use if you are extremely confident that the tree will be set correctly.

Definition at line 251 of file registration.h.

setSearchMethodTarget()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::setSearchMethodTarget	(	const KdTreePtr &	tree,
		bool	force_no_recompute = `false`
	)

inline

Provide a pointer to the search object used to find correspondences in the target cloud.

Parameters

[in]	tree	a pointer to the spatial search object.
[in]	force_no_recompute	If set to true, this tree will NEVER be recomputed, regardless of calls to setInputTarget. Only use if you are confident that the tree will be set correctly.

Definition at line 227 of file registration.h.

setTransformationEpsilon()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::setTransformationEpsilon ( double epsilon )

inline

Set the transformation epsilon (maximum allowable translation squared difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution.

Parameters

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

Definition at line 370 of file registration.h.

setTransformationEstimation()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::setTransformationEstimation ( const TransformationEstimationPtr & te )

inline

Provide a pointer to the transformation estimation object.

(e.g., SVD, point to plane etc.)

Parameters

[in] te is the pointer to the corresponding transformation estimation object

Code example:

TransformationEstimationPointToPlaneLLS<PointXYZ, PointXYZ>::Ptr trans_lls
 (new TransformationEstimationPointToPlaneLLS<PointXYZ, PointXYZ>);
icp.setTransformationEstimation (trans_lls);
// or...
TransformationEstimationSVD<PointXYZ, PointXYZ>::Ptr trans_svd
 (new TransformationEstimationSVD<PointXYZ, PointXYZ>);
icp.setTransformationEstimation (trans_svd);

Definition at line 157 of file registration.h.

setTransformationRotationEpsilon()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::Registration< PointSource, PointTarget, Scalar >::setTransformationRotationEpsilon ( double epsilon )

inline

Set the transformation rotation epsilon (maximum allowable rotation difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution.

Parameters

[in] epsilon the transformation rotation epsilon in order for an optimization to be considered as having converged to the final solution (epsilon is the cos(angle) in a axis-angle representation).

Definition at line 392 of file registration.h.

Member Data Documentation

converged_

template<typename PointSource , typename PointTarget , typename Scalar = float>

bool pcl::Registration< PointSource, PointTarget, Scalar >::converged_

protected

Holds internal convergence state, given user parameters.

Definition at line 623 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::hasConverged().

corr_dist_threshold_

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::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 be ignored in the alignment process.

Definition at line 613 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getMaxCorrespondenceDistance(), and pcl::Registration< PointSource, PointTarget >::setMaxCorrespondenceDistance().

correspondence_estimation_

template<typename PointSource , typename PointTarget , typename Scalar = float>

CorrespondenceEstimationPtr pcl::Registration< PointSource, PointTarget, Scalar >::correspondence_estimation_

protected

A CorrespondenceEstimation object, used to estimate correspondences between the source and the target cloud.

Definition at line 639 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::setCorrespondenceEstimation().

correspondence_rejectors_

template<typename PointSource , typename PointTarget , typename Scalar = float>

std::vector<CorrespondenceRejectorPtr> pcl::Registration< PointSource, PointTarget, Scalar >::correspondence_rejectors_

protected

The list of correspondence rejectors to use.

Definition at line 642 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::addCorrespondenceRejector(), pcl::Registration< PointSource, PointTarget >::clearCorrespondenceRejectors(), pcl::Registration< PointSource, PointTarget >::getCorrespondenceRejectors(), and pcl::Registration< PointSource, PointTarget >::removeCorrespondenceRejector().

correspondences_

template<typename PointSource , typename PointTarget , typename Scalar = float>

CorrespondencesPtr pcl::Registration< PointSource, PointTarget, Scalar >::correspondences_

protected

The set of correspondences determined at this ICP step.

Definition at line 631 of file registration.h.

euclidean_fitness_epsilon_

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::euclidean_fitness_epsilon_

protected

The maximum allowed Euclidean error between two consecutive steps in the ICP loop, before the algorithm is considered to have converged.

The error is estimated as the sum of the differences between correspondences in an Euclidean sense, divided by the number of correspondences.

Definition at line 607 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getEuclideanFitnessEpsilon(), and pcl::Registration< PointSource, PointTarget >::setEuclideanFitnessEpsilon().

final_transformation_

template<typename PointSource , typename PointTarget , typename Scalar = float>

Matrix4 pcl::Registration< PointSource, PointTarget, Scalar >::final_transformation_

protected

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

Definition at line 583 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getFinalTransformation().

force_no_recompute_

template<typename PointSource , typename PointTarget , typename Scalar = float>

bool pcl::Registration< PointSource, PointTarget, Scalar >::force_no_recompute_

protected

A flag which, if set, means the tree operating on the target cloud will never be recomputed.

Definition at line 654 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::setSearchMethodTarget().

force_no_recompute_reciprocal_

template<typename PointSource , typename PointTarget , typename Scalar = float>

bool pcl::Registration< PointSource, PointTarget, Scalar >::force_no_recompute_reciprocal_

protected

A flag which, if set, means the tree operating on the source cloud will never be recomputed.

Definition at line 658 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::setSearchMethodSource().

inlier_threshold_

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::inlier_threshold_

protected

The inlier distance threshold for the internal RANSAC outlier rejection loop.

Definition at line 620 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getRANSACOutlierRejectionThreshold(), and pcl::Registration< PointSource, PointTarget >::setRANSACOutlierRejectionThreshold().

max_iterations_

template<typename PointSource , typename PointTarget , typename Scalar = float>

int pcl::Registration< PointSource, PointTarget, Scalar >::max_iterations_

protected

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

The default value is 10.

Definition at line 573 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getMaximumIterations(), and pcl::Registration< PointSource, PointTarget >::setMaximumIterations().

min_number_correspondences_

template<typename PointSource , typename PointTarget , typename Scalar = float>

int pcl::Registration< PointSource, PointTarget, Scalar >::min_number_correspondences_

protected

The minimum number of correspondences that the algorithm needs before attempting to estimate the transformation.

The default value is 3.

Definition at line 628 of file registration.h.

nr_iterations_

template<typename PointSource , typename PointTarget , typename Scalar = float>

int pcl::Registration< PointSource, PointTarget, Scalar >::nr_iterations_

protected

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

Definition at line 568 of file registration.h.

previous_transformation_

template<typename PointSource , typename PointTarget , typename Scalar = float>

Matrix4 pcl::Registration< PointSource, PointTarget, Scalar >::previous_transformation_

protected

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

Definition at line 590 of file registration.h.

ransac_iterations_

template<typename PointSource , typename PointTarget , typename Scalar = float>

int pcl::Registration< PointSource, PointTarget, Scalar >::ransac_iterations_

protected

The number of iterations RANSAC should run for.

Definition at line 576 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getRANSACIterations(), and pcl::Registration< PointSource, PointTarget >::setRANSACIterations().

reg_name_

template<typename PointSource , typename PointTarget , typename Scalar = float>

std::string pcl::Registration< PointSource, PointTarget, Scalar >::reg_name_

protected

The registration method name.

Definition at line 558 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getClassName().

source_cloud_updated_

template<typename PointSource , typename PointTarget , typename Scalar = float>

bool pcl::Registration< PointSource, PointTarget, Scalar >::source_cloud_updated_

protected

Variable that stores whether we have a new source cloud, meaning we need to pre-process it again.

This way, we avoid rebuilding the reciprocal kd-tree for the source cloud every time the determineCorrespondences () method is called.

Definition at line 651 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::setSearchMethodSource().

target_

template<typename PointSource , typename PointTarget , typename Scalar = float>

PointCloudTargetConstPtr pcl::Registration< PointSource, PointTarget, Scalar >::target_

protected

The input point cloud dataset target.

Definition at line 579 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getInputTarget().

target_cloud_updated_

template<typename PointSource , typename PointTarget , typename Scalar = float>

bool pcl::Registration< PointSource, PointTarget, Scalar >::target_cloud_updated_

protected

Variable that stores whether we have a new target cloud, meaning we need to pre-process it again.

This way, we avoid rebuilding the kd-tree for the target cloud every time the determineCorrespondences () method is called.

Definition at line 647 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::setSearchMethodTarget().

transformation_

template<typename PointSource , typename PointTarget , typename Scalar = float>

Matrix4 pcl::Registration< PointSource, PointTarget, Scalar >::transformation_

protected

The transformation matrix estimated by the registration method.

Definition at line 586 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getLastIncrementalTransformation().

transformation_epsilon_

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::transformation_epsilon_

protected

The maximum difference between two consecutive transformations in order to consider convergence (user defined).

Definition at line 595 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getTransformationEpsilon(), and pcl::Registration< PointSource, PointTarget >::setTransformationEpsilon().

transformation_estimation_

template<typename PointSource , typename PointTarget , typename Scalar = float>

TransformationEstimationPtr pcl::Registration< PointSource, PointTarget, Scalar >::transformation_estimation_

protected

A TransformationEstimation object, used to calculate the 4x4 rigid transformation.

Definition at line 635 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::setTransformationEstimation().

transformation_rotation_epsilon_

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::Registration< PointSource, PointTarget, Scalar >::transformation_rotation_epsilon_

protected

The maximum rotation difference between two consecutive transformations in order to consider convergence (user defined).

Definition at line 600 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getTransformationRotationEpsilon(), and pcl::Registration< PointSource, PointTarget >::setTransformationRotationEpsilon().

tree_

template<typename PointSource , typename PointTarget , typename Scalar = float>

KdTreePtr pcl::Registration< PointSource, PointTarget, Scalar >::tree_

protected

A pointer to the spatial search object.

Definition at line 561 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getSearchMethodTarget(), pcl::Registration< PointSource, PointTarget >::searchForNeighbors(), and pcl::Registration< PointSource, PointTarget >::setSearchMethodTarget().

tree_reciprocal_

template<typename PointSource , typename PointTarget , typename Scalar = float>

KdTreeReciprocalPtr pcl::Registration< PointSource, PointTarget, Scalar >::tree_reciprocal_

protected

A pointer to the spatial search object of the source.

Definition at line 564 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::getSearchMethodSource(), and pcl::Registration< PointSource, PointTarget >::setSearchMethodSource().

update_visualizer_

template<typename PointSource , typename PointTarget , typename Scalar = float>

std::function<UpdateVisualizerCallbackSignature> pcl::Registration< PointSource, PointTarget, Scalar >::update_visualizer_

protected

Callback function to update intermediate source point cloud position during it's registration to the target point cloud.

Definition at line 663 of file registration.h.

Referenced by pcl::Registration< PointSource, PointTarget >::registerVisualizationCallback().

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

pcl/registration/registration.h
pcl/registration/impl/registration.hpp

© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_registration.html

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

template<typename PointSource, typename PointTarget, typename Scalar = float> class pcl::Registration< PointSource, PointTarget, Scalar >

Member Typedef Documentation

ConstPtr

CorrespondenceEstimation

CorrespondenceEstimationConstPtr

CorrespondenceEstimationPtr

CorrespondenceRejectorPtr

KdTree

KdTreePtr

KdTreeReciprocal

KdTreeReciprocalPtr

Matrix4

PointCloudSource

PointCloudSourceConstPtr

PointCloudSourcePtr

PointCloudTarget

PointCloudTargetConstPtr

PointCloudTargetPtr

PointRepresentationConstPtr

Ptr

TransformationEstimation

TransformationEstimationConstPtr

TransformationEstimationPtr

UpdateVisualizerCallbackSignature

Constructor & Destructor Documentation

Registration()

~Registration()

Member Function Documentation

addCorrespondenceRejector()

align() [1/2]

align() [2/2]

clearCorrespondenceRejectors()

computeTransformation()

getClassName()

getCorrespondenceRejectors()

getEuclideanFitnessEpsilon()

getFinalTransformation()

getFitnessScore() [1/2]

getFitnessScore() [2/2]

getInputSource()

getInputTarget()

getLastIncrementalTransformation()

getMaxCorrespondenceDistance()

getMaximumIterations()

getRANSACIterations()

getRANSACOutlierRejectionThreshold()

getSearchMethodSource()

getSearchMethodTarget()

getTransformationEpsilon()

getTransformationRotationEpsilon()

hasConverged()

initCompute()

initComputeReciprocal()

registerVisualizationCallback()

removeCorrespondenceRejector()

searchForNeighbors()

setCorrespondenceEstimation()

setEuclideanFitnessEpsilon()

setInputSource()

setInputTarget()

setMaxCorrespondenceDistance()

setMaximumIterations()

setPointRepresentation()

setRANSACIterations()

setRANSACOutlierRejectionThreshold()

setSearchMethodSource()

setSearchMethodTarget()

setTransformationEpsilon()

setTransformationEstimation()

setTransformationRotationEpsilon()

Member Data Documentation

converged_

corr_dist_threshold_

correspondence_estimation_

correspondence_rejectors_

template<typename PointSource, typename PointTarget, typename Scalar = float>
class pcl::Registration< PointSource, PointTarget, Scalar >