Class that registers two point clouds based on their sets of PPFSignatures. More...

#include <pcl/registration/ppf_registration.h>

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

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

Classes
struct	PoseWithVotes
	Structure for storing a pose (represented as an Eigen::Affine3f) and an integer for counting votes. More...

Public Types
using	PoseWithVotesList
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
Public Types inherited from pcl::Registration< PointSource, PointTarget, Scalar >
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
using	TransformationEstimationPtr = typename TransformationEstimation::Ptr
using	TransformationEstimationConstPtr = typename TransformationEstimation::ConstPtr
using	CorrespondenceEstimation
using	CorrespondenceEstimationPtr = typename CorrespondenceEstimation::Ptr
using	CorrespondenceEstimationConstPtr = typename CorrespondenceEstimation::ConstPtr
using	UpdateVisualizerCallbackSignature
	The callback signature to the function updating intermediate source point cloud position during it's registration to the target point cloud.
Public Types inherited from pcl::PCLBase< PointSource >
using	PointCloud
using	PointCloudPtr
using	PointCloudConstPtr
using	PointIndicesPtr
using	PointIndicesConstPtr

Public Member Functions
	PPFRegistration ()
	Empty constructor that initializes all the parameters of the algorithm with default values.
void	setPositionClusteringThreshold (float clustering_position_diff_threshold)
	Method for setting the position difference clustering parameter.
float	getPositionClusteringThreshold ()
	Returns the parameter defining the position difference clustering parameter.
void	setRotationClusteringThreshold (float clustering_rotation_diff_threshold)
	Method for setting the rotation clustering parameter.
float	getRotationClusteringThreshold ()
	Returns the parameter defining the rotation clustering threshold.
void	setSceneReferencePointSamplingRate (unsigned int scene_reference_point_sampling_rate)
	Method for setting the scene reference point sampling rate.
unsigned int	getSceneReferencePointSamplingRate ()
	Returns the parameter for the scene reference point sampling rate of the algorithm.
void	setSearchMethod (PPFHashMapSearch::Ptr search_method)
	Function that sets the search method for the algorithm.
PPFHashMapSearch::Ptr	getSearchMethod ()
	Getter function for the search method of the class.
void	setInputTarget (const PointCloudTargetConstPtr &cloud) override
	Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to).
Public Member Functions inherited from pcl::Registration< PointSource, PointTarget, Scalar >
	Registration ()
	Empty constructor.
	~Registration ()
	destructor.
void	setTransformationEstimation (const TransformationEstimationPtr &te)
	Provide a pointer to the transformation estimation object.
void	setCorrespondenceEstimation (const CorrespondenceEstimationPtr &ce)
	Provide a pointer to the correspondence estimation object.
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).
PointCloudSourceConstPtr const	getInputSource ()
	Get a pointer to the input point cloud dataset target.
PointCloudTargetConstPtr const	getInputTarget ()
	Get a pointer to the input point cloud dataset target.
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.
KdTreePtr	getSearchMethodTarget () const
	Get a pointer to the search method used to find correspondences in the target cloud.
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).
KdTreeReciprocalPtr	getSearchMethodSource () const
	Get a pointer to the search method used to find correspondences in the source cloud.
Matrix4	getFinalTransformation ()
	Get the final transformation matrix estimated by the registration method.
Matrix4	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	setRANSACIterations (int ransac_iterations)
	Set the number of iterations RANSAC should run for.
double	getRANSACIterations ()
	Get the number of iterations RANSAC 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 translation squared 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 translation squared difference between two consecutive transformations) as set by the user.
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.
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).
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.
double	getEuclideanFitnessEpsilon ()
	Get the maximum allowed distance error before the algorithm will be considered to have converged, 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.
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.
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).
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).
bool	hasConverged () const
	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 Matrix4 &guess)
	Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output.
const std::string &	getClassName () const
	Abstract class get name method.
bool	initCompute ()
	Internal computation initialization.
bool	initComputeReciprocal ()
	Internal computation when reciprocal lookup is needed.
void	addCorrespondenceRejector (const CorrespondenceRejectorPtr &rejector)
	Add a new correspondence rejector to the list.
std::vector< CorrespondenceRejectorPtr >	getCorrespondenceRejectors ()
	Get the list of correspondence rejectors.
bool	removeCorrespondenceRejector (unsigned int i)
	Remove the i-th correspondence rejector in the list.
void	clearCorrespondenceRejectors ()
	Clear the list of correspondence rejectors.
Public Member Functions inherited from pcl::PCLBase< PointSource >
	PCLBase ()
	Empty constructor.
virtual	~PCLBase ()=default
	Destructor.
virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset.
PointCloudConstPtr const	getInputCloud () const
	Get a pointer to the input point cloud dataset.
virtual void	setIndices (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.
IndicesPtr	getIndices ()
	Get a pointer to the vector of indices used.
const PointSource &	operator[] (std::size_t pos) const
	Override PointCloud operator[] to shorten code.

Additional Inherited Members
Protected Member Functions inherited from pcl::Registration< PointSource, PointTarget, Scalar >
bool	searchForNeighbors (const PointCloudSource &cloud, int index, pcl::Indices &indices, std::vector< float > &distances)
	Search for the closest nearest neighbor of a given point.
virtual void	computeTransformation (PointCloudSource &output, const Matrix4 &guess)=0
	Abstract transformation computation method with initial guess.
Protected Member Functions inherited from pcl::PCLBase< PointSource >
bool	initCompute ()
	This method should get called before starting the actual computation.
bool	deinitCompute ()
	This method should get called after finishing the actual computation.
Protected Attributes inherited from pcl::Registration< PointSource, PointTarget, Scalar >
std::string	reg_name_
	The registration method name.
KdTreePtr	tree_
	A pointer to the spatial search object.
KdTreeReciprocalPtr	tree_reciprocal_
	A pointer to the spatial search object of the source.
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.
int	ransac_iterations_
	The number of iterations RANSAC should run for.
PointCloudTargetConstPtr	target_
	The input point cloud dataset target.
Matrix4	final_transformation_
	The final transformation matrix estimated by the registration method after N iterations.
Matrix4	transformation_
	The transformation matrix estimated by the registration method.
Matrix4	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	transformation_rotation_epsilon_
	The maximum rotation difference between two consecutive transformations in order to consider convergence (user defined).
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.
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.
CorrespondencesPtr	correspondences_
	The set of correspondences determined at this ICP step.
TransformationEstimationPtr	transformation_estimation_
	A TransformationEstimation object, used to calculate the 4x4 rigid transformation.
CorrespondenceEstimationPtr	correspondence_estimation_
	A CorrespondenceEstimation object, used to estimate correspondences between the source and the target cloud.
std::vector< CorrespondenceRejectorPtr >	correspondence_rejectors_
	The list of correspondence rejectors to use.
bool	target_cloud_updated_
	Variable that stores whether we have a new target cloud, meaning we need to pre-process it again.
bool	source_cloud_updated_
	Variable that stores whether we have a new source cloud, meaning we need to pre-process it again.
bool	force_no_recompute_
	A flag which, if set, means the tree operating on the target cloud will never be recomputed.
bool	force_no_recompute_reciprocal_
	A flag which, if set, means the tree operating on the source cloud will never be recomputed.
std::function< UpdateVisualizerCallbackSignature >	update_visualizer_
	Callback function to update intermediate source point cloud position during it's registration to the target point cloud.
Protected Attributes inherited from pcl::PCLBase< PointSource >
PointCloudConstPtr	input_
	The input point cloud dataset.
IndicesPtr	indices_
	A pointer to the vector of point indices to use.
bool	use_indices_
	Set to true if point indices are used.
bool	fake_indices_
	If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud.

Detailed Description

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

Class that registers two point clouds based on their sets of PPFSignatures.

Please refer to the following publication for more details: B. Drost, M. Ulrich, N. Navab, S. Ilic Model Globally, Match Locally: Efficient and Robust 3D Object Recognition 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 13-18 June 2010, San Francisco, CA

Note: This class works in tandem with the PPFEstimation class

Author: Alexandru-Eugen Ichim

Definition at line 176 of file ppf_registration.h.

Member Typedef Documentation

◆ PointCloudSource

template<typename PointSource, typename PointTarget>

using pcl::PPFRegistration< PointSource, PointTarget >::PointCloudSource = pcl::PointCloud<PointSource>

Definition at line 202 of file ppf_registration.h.

◆ PointCloudSourceConstPtr

template<typename PointSource, typename PointTarget>

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

Definition at line 204 of file ppf_registration.h.

◆ PointCloudSourcePtr

template<typename PointSource, typename PointTarget>

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

Definition at line 203 of file ppf_registration.h.

◆ PointCloudTarget

template<typename PointSource, typename PointTarget>

using pcl::PPFRegistration< PointSource, PointTarget >::PointCloudTarget = pcl::PointCloud<PointTarget>

Definition at line 206 of file ppf_registration.h.

◆ PointCloudTargetConstPtr

template<typename PointSource, typename PointTarget>

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

Definition at line 208 of file ppf_registration.h.

◆ PointCloudTargetPtr

template<typename PointSource, typename PointTarget>

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

Definition at line 207 of file ppf_registration.h.

◆ PoseWithVotesList

template<typename PointSource, typename PointTarget>

using pcl::PPFRegistration< PointSource, PointTarget >::PoseWithVotesList

Initial value:

std::vector<PoseWithVotes, Eigen::aligned_allocator<PoseWithVotes>>

Definition at line 191 of file ppf_registration.h.

Constructor & Destructor Documentation

◆ PPFRegistration()

template<typename PointSource, typename PointTarget>

pcl::PPFRegistration< PointSource, PointTarget >::PPFRegistration ( )

inline

Empty constructor that initializes all the parameters of the algorithm with default values.

Definition at line 212 of file ppf_registration.h.

References M_PI, and pcl::Registration< PointSource, PointTarget, Scalar >::Registration().

Member Function Documentation

◆ getPositionClusteringThreshold()

template<typename PointSource, typename PointTarget>

float pcl::PPFRegistration< PointSource, PointTarget >::getPositionClusteringThreshold ( )

inline

Returns the parameter defining the position difference clustering parameter.

distance threshold below which two poses are considered close enough to be in the same cluster (for the clustering phase of the algorithm)

Definition at line 235 of file ppf_registration.h.

◆ getRotationClusteringThreshold()

template<typename PointSource, typename PointTarget>

float pcl::PPFRegistration< PointSource, PointTarget >::getRotationClusteringThreshold ( )

inline

Returns the parameter defining the rotation clustering threshold.

Definition at line 254 of file ppf_registration.h.

◆ getSceneReferencePointSamplingRate()

template<typename PointSource, typename PointTarget>

unsigned int pcl::PPFRegistration< PointSource, PointTarget >::getSceneReferencePointSamplingRate ( )

inline

Returns the parameter for the scene reference point sampling rate of the algorithm.

Definition at line 272 of file ppf_registration.h.

◆ getSearchMethod()

template<typename PointSource, typename PointTarget>

PPFHashMapSearch::Ptr pcl::PPFRegistration< PointSource, PointTarget >::getSearchMethod ( )

inline

Getter function for the search method of the class.

Definition at line 290 of file ppf_registration.h.

◆ setInputTarget()

template<typename PointSource, typename PointTarget>

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

overridevirtual

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

Reimplemented from pcl::Registration< PointSource, PointTarget, Scalar >.

Definition at line 53 of file ppf_registration.hpp.

References pcl::Registration< PointSource, PointTarget, Scalar >::setInputTarget(), and pcl::Registration< PointSource, PointTarget, Scalar >::target_.

◆ setPositionClusteringThreshold()

template<typename PointSource, typename PointTarget>

void pcl::PPFRegistration< PointSource, PointTarget >::setPositionClusteringThreshold ( float clustering_position_diff_threshold )

inline

Method for setting the position difference clustering parameter.

Parameters

clustering_position_diff_threshold distance threshold below which two poses are considered close enough to be in the same cluster (for the clustering phase of the algorithm)

Definition at line 225 of file ppf_registration.h.

◆ setRotationClusteringThreshold()

template<typename PointSource, typename PointTarget>

void pcl::PPFRegistration< PointSource, PointTarget >::setRotationClusteringThreshold ( float clustering_rotation_diff_threshold )

inline

Method for setting the rotation clustering parameter.

Parameters

clustering_rotation_diff_threshold rotation difference threshold below which two poses are considered to be in the same cluster (for the clustering phase of the algorithm)

Definition at line 246 of file ppf_registration.h.

◆ setSceneReferencePointSamplingRate()

template<typename PointSource, typename PointTarget>

void pcl::PPFRegistration< PointSource, PointTarget >::setSceneReferencePointSamplingRate ( unsigned int scene_reference_point_sampling_rate )

inline

Method for setting the scene reference point sampling rate.

Parameters

scene_reference_point_sampling_rate sampling rate for the scene reference point

Definition at line 264 of file ppf_registration.h.

◆ setSearchMethod()

template<typename PointSource, typename PointTarget>

void pcl::PPFRegistration< PointSource, PointTarget >::setSearchMethod ( PPFHashMapSearch::Ptr search_method )

inline

Function that sets the search method for the algorithm.

Note: Right now, the only available method is the one initially proposed by the authors - by using a hash map with discretized feature vectors

Parameters

search_method smart pointer to the search method to be set

Definition at line 283 of file ppf_registration.h.

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

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

Classes

Public Types

Public Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ PointCloudSource

◆ PointCloudSourceConstPtr

◆ PointCloudSourcePtr

◆ PointCloudTarget

◆ PointCloudTargetConstPtr

◆ PointCloudTargetPtr

◆ PoseWithVotesList

Constructor & Destructor Documentation

◆ PPFRegistration()

Member Function Documentation

◆ getPositionClusteringThreshold()

◆ getRotationClusteringThreshold()

◆ getSceneReferencePointSamplingRate()

◆ getSearchMethod()

◆ setInputTarget()

◆ setPositionClusteringThreshold()

◆ setRotationClusteringThreshold()

◆ setSceneReferencePointSamplingRate()

◆ setSearchMethod()