KFPCSInitialAlignment computes corresponding four point congruent sets based on keypoints as described in: "Markerless point cloud registration with keypoint-based 4-points congruent sets", Pascal Theiler, Jan Dirk Wegner, Konrad Schindler. More...

#include <pcl/registration/ia_kfpcs.h>

Inheritance diagram for pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >:

Collaboration diagram for pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >:

Public Member Functions
	KFPCSInitialAlignment ()
	Constructor. More...

	~KFPCSInitialAlignment () override=default
	Destructor. More...

void	setUpperTranslationThreshold (float upper_trl_boundary)
	Set the upper translation threshold used for score evaluation. More...

float	getUpperTranslationThreshold () const

void	setLowerTranslationThreshold (float lower_trl_boundary)
	Set the lower translation threshold used for score evaluation. More...

float	getLowerTranslationThreshold () const

void	setLambda (float lambda)
	Set the weighting factor of the translation cost term. More...

float	getLambda () const

void	getNBestCandidates (int n, float min_angle3d, float min_translation3d, MatchingCandidates &candidates)
	Get the N best unique candidate matches according to their fitness score. More...

void	getTBestCandidates (float t, float min_angle3d, float min_translation3d, MatchingCandidates &candidates)
	Get all unique candidate matches with fitness scores above a threshold t. More...

Public Member Functions inherited from pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >
	FPCSInitialAlignment ()
	Constructor. More...

	~FPCSInitialAlignment () override=default
	Destructor. More...

void	setTargetIndices (const IndicesPtr &target_indices)
	Provide a pointer to the vector of target indices. More...

IndicesPtr	getTargetIndices () const

void	setSourceNormals (const NormalsConstPtr &source_normals)
	Provide a pointer to the normals of the source point cloud. More...

NormalsConstPtr	getSourceNormals () const

void	setTargetNormals (const NormalsConstPtr &target_normals)
	Provide a pointer to the normals of the target point cloud. More...

NormalsConstPtr	getTargetNormals () const

void	setNumberOfThreads (int nr_threads)
	Set the number of used threads if OpenMP is activated. More...

int	getNumberOfThreads () const

void	setDelta (float delta, bool normalize=false)
	Set the constant factor delta which weights the internally calculated parameters. More...

float	getDelta () const

void	setApproxOverlap (float approx_overlap)
	Set the approximate overlap between source and target. More...

float	getApproxOverlap () const

void	setScoreThreshold (float score_threshold)
	Set the scoring threshold used for early finishing the method. More...

float	getScoreThreshold () const

void	setNumberOfSamples (int nr_samples)
	Set the number of source samples to use during alignment. More...

int	getNumberOfSamples () const

void	setMaxNormalDifference (float max_norm_diff)
	Set the maximum normal difference between valid point correspondences in degree. More...

float	getMaxNormalDifference () const

void	setMaxComputationTime (int max_runtime)
	Set the maximum computation time in seconds. More...

int	getMaxComputationTime () const

float	getFitnessScore () const

Public Member Functions inherited from pcl::Registration< PointSource, PointTarget, float >
	Registration ()
	Empty constructor. More...

	~Registration () override=default
	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...

PointCloudSourceConstPtr const	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...

PointCloudTargetConstPtr const	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...

PointCloudConstPtr const	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...

IndicesConstPtr const	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	initCompute () override
	Internal computation initialization. More...

void	handleMatches (const pcl::Indices &base_indices, std::vector< pcl::Indices > &matches, MatchingCandidates &candidates) override
	Method to handle current candidate matches. More...

int	validateTransformation (Eigen::Matrix4f &transformation, float &fitness_score) override
	Validate the transformation by calculating the score value after transforming the input source cloud. More...

void	finalCompute (const std::vector< MatchingCandidates > &candidates) override
	Final computation of best match out of vector of matches. More...

Protected Member Functions inherited from pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >
void	computeTransformation (PointCloudSource &output, const Eigen::Matrix4f &guess) override
	Rigid transformation computation method. More...

int	selectBase (pcl::Indices &base_indices, float(&ratio)[2])
	Select an approximately coplanar set of four points from the source cloud. More...

int	selectBaseTriangle (pcl::Indices &base_indices)
	Select randomly a triplet of points with large point-to-point distances. More...

void	setupBase (pcl::Indices &base_indices, float(&ratio)[2])
	Setup the base (four coplanar points) by ordering the points and computing intersection ratios and segment to segment distances of base diagonal. More...

float	segmentToSegmentDist (const pcl::Indices &base_indices, float(&ratio)[2])
	Calculate intersection ratios and segment to segment distances of base diagonals. More...

virtual int	bruteForceCorrespondences (int idx1, int idx2, pcl::Correspondences &pairs)
	Search for corresponding point pairs given the distance between two base points. More...

virtual int	determineBaseMatches (const pcl::Indices &base_indices, std::vector< pcl::Indices > &matches, const pcl::Correspondences &pairs_a, const pcl::Correspondences &pairs_b, const float(&ratio)[2])
	Determine base matches by combining the point pair candidate and search for coinciding intersection points using the diagonal segment ratios of base B. More...

int	checkBaseMatch (const pcl::Indices &match_indices, const float(&ds)[4])
	Check if outer rectangle distance of matched points fit with the base rectangle. More...

virtual void	linkMatchWithBase (const pcl::Indices &base_indices, pcl::Indices &match_indices, pcl::Correspondences &correspondences)
	Sets the correspondences between the base B and the match M by using the distance of each point to the centroid of the rectangle. More...

virtual int	validateMatch (const pcl::Indices &base_indices, const pcl::Indices &match_indices, const pcl::Correspondences &correspondences, Eigen::Matrix4f &transformation)
	Validate the matching by computing the transformation between the source and target based on the four matched points and by comparing the mean square error (MSE) to a threshold. More...

Protected Member Functions inherited from pcl::Registration< PointSource, PointTarget, float >
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
float	lower_trl_boundary_ {-1.f}
	Lower boundary for translation costs calculation. More...

float	upper_trl_boundary_ {-1.f}
	Upper boundary for translation costs calculation. More...

float	lambda_ {0.5f}
	Weighting factor for translation costs (standard = 0.5). More...

MatchingCandidates	candidates_
	Container for resulting vector of registration candidates. More...

bool	use_trl_score_ {false}
	Flag if translation score should be used in validation (internal calculation). More...

pcl::IndicesPtr	indices_validation_
	Subset of input indices on which we evaluate candidates. More...

Protected Attributes inherited from pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >
NormalsConstPtr	source_normals_
	Normals of source point cloud. More...

NormalsConstPtr	target_normals_
	Normals of target point cloud. More...

int	nr_threads_
	Number of threads for parallelization (standard = 1). More...

float	approx_overlap_
	Estimated overlap between source and target (standard = 0.5). More...

float	delta_
	Delta value of 4pcs algorithm (standard = 1.0). More...

float	score_threshold_
	Score threshold to stop calculation with success. More...

int	nr_samples_
	The number of points to uniformly sample the source point cloud. More...

float	max_norm_diff_
	Maximum normal difference of corresponding point pairs in degrees (standard = 90). More...

int	max_runtime_
	Maximum allowed computation time in seconds (standard = 0 => ~unlimited). More...

float	fitness_score_
	Resulting fitness score of the best match. More...

float	diameter_
	Estimated diameter of the target point cloud. More...

float	max_base_diameter_sqr_
	Estimated squared metric overlap between source and target. More...

bool	use_normals_
	Use normals flag. More...

bool	normalize_delta_
	Normalize delta flag. More...

pcl::IndicesPtr	source_indices_
	A pointer to the vector of source point indices to use after sampling. More...

pcl::IndicesPtr	target_indices_
	A pointer to the vector of target point indices to use after sampling. More...

float	max_pair_diff_
	Maximal difference between corresponding point pairs in source and target. More...

float	max_edge_diff_
	Maximal difference between the length of the base edges and valid match edges. More...

float	coincidation_limit_
	Maximal distance between coinciding intersection points to find valid matches. More...

float	max_mse_
	Maximal mean squared errors of a transformation calculated from a candidate match. More...

float	max_inlier_dist_sqr_
	Maximal squared point distance between source and target points to count as inlier. More...

const float	small_error_
	Definition of a small error. More...

Protected Attributes inherited from pcl::Registration< PointSource, PointTarget, float >
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...

unsigned 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...

Additional Inherited Members
Public Types inherited from pcl::Registration< PointSource, PointTarget, float >
using	Matrix4 = Eigen::Matrix< float, 4, 4 >

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

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

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, float >

using	TransformationEstimationPtr = typename TransformationEstimation::Ptr

using	TransformationEstimationConstPtr = typename TransformationEstimation::ConstPtr

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

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

Detailed Description

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
class pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >

KFPCSInitialAlignment computes corresponding four point congruent sets based on keypoints as described in: "Markerless point cloud registration with keypoint-based 4-points congruent sets", Pascal Theiler, Jan Dirk Wegner, Konrad Schindler.

ISPRS Annals II-5/W2, 2013. Presented at ISPRS Workshop Laser Scanning, Antalya, Turkey, 2013.

Note: Method has since been improved and some variations to the paper exist.

The main differences to FPCSInitialAlignment are:

KFPCSInitialAlignment stores all solution candidates instead of only the best one
KFPCSInitialAlignment uses an MSAC approach to score candidates instead of counting inliers

Author: P.W.Theiler

Definition at line 64 of file ia_kfpcs.h.

Constructor & Destructor Documentation

◆ KFPCSInitialAlignment()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >

pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::KFPCSInitialAlignment

Constructor.

Definition at line 47 of file ia_kfpcs.hpp.

References pcl::Registration< PointSource, PointTarget, float >::reg_name_.

◆ ~KFPCSInitialAlignment()

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::~KFPCSInitialAlignment ( )

overridedefault

Destructor.

Member Function Documentation

◆ finalCompute()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >

void pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::finalCompute ( const std::vector< MatchingCandidates > & candidates )

overrideprotectedvirtual

Final computation of best match out of vector of matches.

To avoid cross thread dependencies during parallel running, a best match for each try was calculated.

Note: For forwards compatibility the candidates are stored in vectors of 'vectors of size 1'.

Parameters

[in] candidates vector of candidate matches

Reimplemented from pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >.

Definition at line 215 of file ia_kfpcs.hpp.

◆ getLambda()

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

float pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getLambda ( ) const

inline

Returns: the weighting factor of the translation cost term.

Definition at line 134 of file ia_kfpcs.h.

References pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::lambda_.

◆ getLowerTranslationThreshold()

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

float pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getLowerTranslationThreshold ( ) const

inline

Returns: the lower translation threshold used for score evaluation.

Definition at line 118 of file ia_kfpcs.h.

References pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::lower_trl_boundary_.

◆ getNBestCandidates()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >

void pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getNBestCandidates	(	int	n,
		float	min_angle3d,
		float	min_translation3d,
		MatchingCandidates &	candidates
	)

Get the N best unique candidate matches according to their fitness score.

The method only returns unique transformations comparing the translation and the 3D rotation to already returned transformations.

Note: The method may return less than N candidates, if the number of unique candidates is smaller than N

Parameters

[in]	n	number of best candidates to return
[in]	min_angle3d	minimum 3D angle difference in radian
[in]	min_translation3d	minimum 3D translation difference
[out]	candidates	vector of unique candidates

Definition at line 257 of file ia_kfpcs.hpp.

◆ getTBestCandidates()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >

void pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getTBestCandidates	(	float	t,
		float	min_angle3d,
		float	min_translation3d,
		MatchingCandidates &	candidates
	)

Get all unique candidate matches with fitness scores above a threshold t.

The method only returns unique transformations comparing the translation and the 3D rotation to already returned transformations.

Parameters

[in]	t	fitness score threshold
[in]	min_angle3d	minimum 3D angle difference in radian
[in]	min_translation3d	minimum 3D translation difference
[out]	candidates	vector of unique candidates

Definition at line 294 of file ia_kfpcs.hpp.

◆ getUpperTranslationThreshold()

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

float pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getUpperTranslationThreshold ( ) const

inline

Returns: the upper translation threshold used for score evaluation.

Definition at line 102 of file ia_kfpcs.h.

References pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::upper_trl_boundary_.

◆ handleMatches()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >

void pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::handleMatches	(	const pcl::Indices &	base_indices,
		std::vector< pcl::Indices > &	matches,
		MatchingCandidates &	candidates
	)

overrideprotectedvirtual

Method to handle current candidate matches.

Here we validate and evaluate the matches w.r.t the base and store the sorted matches (together with score values and estimated transformations).

Parameters

[in]	base_indices	indices of base B
[in,out]	matches	vector of candidate matches w.r.t the base B. The candidate matches are reordered during this step.
[out]	candidates	vector which contains the candidates matches M

Reimplemented from pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >.

Definition at line 118 of file ia_kfpcs.hpp.

◆ initCompute()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >

bool pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::initCompute

overrideprotectedvirtual

Internal computation initialization.

Reimplemented from pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >.

Definition at line 56 of file ia_kfpcs.hpp.

References pcl::FilterIndices< PointT >::filter(), pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::initCompute(), pcl::PCLBase< PointT >::setIndices(), pcl::PCLBase< PointT >::setInputCloud(), and pcl::RandomSample< PointT >::setSample().

◆ setLambda()

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

void pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setLambda ( float lambda )

inline

Set the weighting factor of the translation cost term.

Parameters

[in] lambda the weighting factor of the translation cost term

Definition at line 127 of file ia_kfpcs.h.

References pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::lambda_.

◆ setLowerTranslationThreshold()

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

void pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setLowerTranslationThreshold ( float lower_trl_boundary )

inline

Set the lower translation threshold used for score evaluation.

Parameters

[in] lower_trl_boundary lower translation threshold

Definition at line 111 of file ia_kfpcs.h.

References pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::lower_trl_boundary_.

◆ setUpperTranslationThreshold()

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

void pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setUpperTranslationThreshold ( float upper_trl_boundary )

inline

Set the upper translation threshold used for score evaluation.

Parameters

[in] upper_trl_boundary upper translation threshold

Definition at line 95 of file ia_kfpcs.h.

References pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::upper_trl_boundary_.

◆ validateTransformation()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >

int pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation	(	Eigen::Matrix4f &	transformation,
		float &	fitness_score
	)

overrideprotectedvirtual

Validate the transformation by calculating the score value after transforming the input source cloud.

The resulting score is later used as the decision criteria of the best fitting match.

Parameters

[out]	transformation	updated orientation matrix using all inliers
[out]	fitness_score	current best score

Note: fitness score is only updated if the score of the current transformation exceeds the input one.

Returns

< 0 if previous result is better than the current one (score remains)
= 0 current result is better than the previous one (score updated)

Reimplemented from pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >.

Definition at line 164 of file ia_kfpcs.hpp.

References M_PI, M_PI_2, pcl::PointCloud< PointT >::size(), and pcl::transformPointCloud().

Member Data Documentation

◆ candidates_

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

MatchingCandidates pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::candidates_

protected

Container for resulting vector of registration candidates.

Definition at line 258 of file ia_kfpcs.h.

◆ indices_validation_

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

pcl::IndicesPtr pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::indices_validation_

protected

Subset of input indices on which we evaluate candidates.

To speed up the evaluation, we only use a fix number of indices defined during initialization.

Definition at line 268 of file ia_kfpcs.h.

◆ lambda_

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

float pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::lambda_ {0.5f}

protected

Weighting factor for translation costs (standard = 0.5).

Definition at line 255 of file ia_kfpcs.h.

Referenced by pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getLambda(), and pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setLambda().

◆ lower_trl_boundary_

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

float pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::lower_trl_boundary_ {-1.f}

protected

Lower boundary for translation costs calculation.

Note: If not set by the user, the translation costs are not used during evaluation.

Definition at line 246 of file ia_kfpcs.h.

Referenced by pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getLowerTranslationThreshold(), and pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setLowerTranslationThreshold().

◆ upper_trl_boundary_

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

float pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::upper_trl_boundary_ {-1.f}

protected

Upper boundary for translation costs calculation.

Note: If not set by the user, it is calculated from the estimated overlap and the diameter of the point cloud.

Definition at line 252 of file ia_kfpcs.h.

Referenced by pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getUpperTranslationThreshold(), and pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setUpperTranslationThreshold().

◆ use_trl_score_

template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>

bool pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::use_trl_score_ {false}

protected

Flag if translation score should be used in validation (internal calculation).

Definition at line 262 of file ia_kfpcs.h.

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

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

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float> class pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >

Constructor & Destructor Documentation

◆ KFPCSInitialAlignment()

◆ ~KFPCSInitialAlignment()

Member Function Documentation

◆ finalCompute()

◆ getLambda()

◆ getLowerTranslationThreshold()

◆ getNBestCandidates()

◆ getTBestCandidates()

◆ getUpperTranslationThreshold()

◆ handleMatches()

◆ initCompute()

◆ setLambda()

◆ setLowerTranslationThreshold()

◆ setUpperTranslationThreshold()

◆ validateTransformation()

Member Data Documentation

◆ candidates_

◆ indices_validation_

◆ lambda_

◆ lower_trl_boundary_

◆ upper_trl_boundary_

◆ use_trl_score_

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
class pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >