Point Cloud Library (PCL): pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar

FPCSInitialAlignment computes corresponding four point congruent sets as described in: "4-points congruent sets for robust pairwise surface registration", Dror Aiger, Niloy Mitra, Daniel Cohen-Or. More...

#include <pcl/registration/ia_fpcs.h>

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

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

	~FPCSInitialAlignment ()
	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 ()
	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
void	computeTransformation (PointCloudSource &output, const Eigen::Matrix4f &guess) override
	Rigid transformation computation method. More...

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

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

int	selectBaseTriangle (std::vector< int > &base_indices)
	Select randomly a triplet of points with large point-to-point distances. More...

void	setupBase (std::vector< int > &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 std::vector< int > &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 std::vector< int > &base_indices, std::vector< std::vector< int >> &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 std::vector< int > &match_indices, const float(&ds)[4])
	Check if outer rectangle distance of matched points fit with the base rectangle. More...

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

virtual void	linkMatchWithBase (const std::vector< int > &base_indices, std::vector< int > &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 std::vector< int > &base_indices, const std::vector< int > &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...

virtual int	validateTransformation (Eigen::Matrix4f &transformation, float &fitness_score)
	Validate the transformation by calculating the number of inliers after transforming the source cloud. More...

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

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

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 std::vector< int > &, const pcl::PointCloud< PointTarget > &, const std::vector< int > &)
	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::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >

FPCSInitialAlignment computes corresponding four point congruent sets as described in: "4-points congruent sets for robust pairwise surface registration", Dror Aiger, Niloy Mitra, Daniel Cohen-Or.

ACM Transactions on Graphics, vol. 27(3), 2008

Author: P.W.Theiler

Definition at line 81 of file ia_fpcs.h.

Constructor & Destructor Documentation

◆ FPCSInitialAlignment()

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

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

Constructor.

Resets the maximum number of iterations to 0 thus forcing an internal computation if not set by the user. Sets the number of RANSAC iterations to 1000 and the standard transformation estimation to TransformationEstimation3Point.

Definition at line 134 of file ia_fpcs.hpp.

◆ ~FPCSInitialAlignment()

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

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

inline

Destructor.

Definition at line 112 of file ia_fpcs.h.

Member Function Documentation

◆ bruteForceCorrespondences()

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::bruteForceCorrespondences	(	int	idx1,
		int	idx2,
		pcl::Correspondences &	pairs
	)

protectedvirtual

Search for corresponding point pairs given the distance between two base points.

Parameters

[in]	idx1	first index of current base segment (in source cloud)
[in]	idx2	second index of current base segment (in source cloud)
[out]	pairs	resulting point pairs with point-to-point distance close to ref_dist

Returns

< 0 no corresponding point pair was found
= 0 at least one point pair candidate was found

Definition at line 578 of file ia_fpcs.hpp.

◆ checkBaseMatch()

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::checkBaseMatch	(	const std::vector< int > &	match_indices,
		const float(&)	ds[4]
	)

protected

Check if outer rectangle distance of matched points fit with the base rectangle.

Parameters

[in]	match_indices	indices of match M
[in]	ds	edge lengths of base B

Returns

< 0 at least one edge of the match M has no corresponding one in the base B
= 0 edges of match M fits to the ones of base B

Definition at line 714 of file ia_fpcs.hpp.

◆ computeTransformation()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::computeTransformation	(	PointCloudSource &	output,
		const Eigen::Matrix4f &	guess
	)

overrideprotected

Rigid transformation computation method.

Parameters

output	the transformed input point cloud dataset using the rigid transformation found
guess	The computed transforamtion

Definition at line 167 of file ia_fpcs.hpp.

◆ determineBaseMatches()

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::determineBaseMatches	(	const std::vector< int > &	base_indices,
		std::vector< std::vector< int >> &	matches,
		const pcl::Correspondences &	pairs_a,
		const pcl::Correspondences &	pairs_b,
		const float(&)	ratio[2]
	)

protectedvirtual

Determine base matches by combining the point pair candidate and search for coinciding intersection points using the diagonal segment ratios of base B.

The coincidation threshold is calculated during initialization (coincidation_limit_).

Parameters

[in]	base_indices	indices of base B
[out]	matches	vector of candidate matches w.r.t the base B
[in]	pairs_a	point pairs corresponding to points of 1st diagonal of base B
[in]	pairs_b	point pairs corresponding to points of 2nd diagonal of base B
[in]	ratio	diagonal intersection ratios of base points

Returns

< 0 no base match could be found
= 0 at least one base match was found

Definition at line 632 of file ia_fpcs.hpp.

◆ finalCompute()

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

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

protectedvirtual

Final computation of best match out of vector of best 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 in pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >.

Definition at line 903 of file ia_fpcs.hpp.

◆ getApproxOverlap()

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getApproxOverlap ( ) const

inline

Returns: the approximated overlap between source and target.

Definition at line 208 of file ia_fpcs.h.

◆ getDelta()

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getDelta ( ) const

inline

Returns: the constant factor delta which weights the internally calculated parameters.

Definition at line 192 of file ia_fpcs.h.

◆ getFitnessScore()

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getFitnessScore ( ) const

inline

Returns: the fitness score of the best scored four-point match.

Definition at line 280 of file ia_fpcs.h.

◆ getMaxComputationTime()

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getMaxComputationTime ( ) const

inline

Returns: the maximum computation time in seconds.

Definition at line 273 of file ia_fpcs.h.

◆ getMaxNormalDifference()

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getMaxNormalDifference ( ) const

inline

Returns: the maximum normal difference between valid point correspondences in degree.

Definition at line 257 of file ia_fpcs.h.

◆ getNumberOfSamples()

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getNumberOfSamples ( ) const

inline

Returns: the number of source samples to use during alignment.

Definition at line 240 of file ia_fpcs.h.

◆ getNumberOfThreads()

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getNumberOfThreads ( ) const

inline

Returns: the number of threads used if OpenMP is activated.

Definition at line 173 of file ia_fpcs.h.

◆ getScoreThreshold()

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getScoreThreshold ( ) const

inline

Returns: the scoring threshold used for early finishing the method.

Definition at line 224 of file ia_fpcs.h.

◆ getSourceNormals()

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

NormalsConstPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getSourceNormals ( ) const

inline

Returns: the normals of the source point cloud.

Definition at line 141 of file ia_fpcs.h.

◆ getTargetIndices()

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

IndicesPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getTargetIndices ( ) const

inline

Returns: a pointer to the vector of target indices.

Definition at line 125 of file ia_fpcs.h.

◆ getTargetNormals()

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

NormalsConstPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getTargetNormals ( ) const

inline

Returns: the normals of the target point cloud.

Definition at line 157 of file ia_fpcs.h.

◆ handleMatches()

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

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

protectedvirtual

Method to handle current candidate matches.

Here we validate and evaluate the matches w.r.t the base and store the best fitting match (together with its score and estimated transformation).

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

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

Definition at line 738 of file ia_fpcs.hpp.

◆ initCompute()

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

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

protectedvirtual

Internal computation initialization.

Reimplemented in pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >.

Definition at line 237 of file ia_fpcs.hpp.

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

◆ linkMatchWithBase()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::linkMatchWithBase	(	const std::vector< int > &	base_indices,
		std::vector< int > &	match_indices,
		pcl::Correspondences &	correspondences
	)

protectedvirtual

Sets the correspondences between the base B and the match M by using the distance of each point to the centroid of the rectangle.

Parameters

[in]	base_indices	indices of base B
[in]	match_indices	indices of match M
[out]	correspondences	resulting correspondences

Definition at line 776 of file ia_fpcs.hpp.

◆ segmentToSegmentDist()

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::segmentToSegmentDist	(	const std::vector< int > &	base_indices,
		float(&)	ratio[2]
	)

protected

Calculate intersection ratios and segment to segment distances of base diagonals.

Parameters

[in]	base_indices	indices of base B
[out]	ratio	diagonal intersection ratios of base points

Returns: quality value of diagonal intersection

Definition at line 493 of file ia_fpcs.hpp.

◆ selectBase()

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::selectBase	(	std::vector< int > &	base_indices,
		float(&)	ratio[2]
	)

protected

Select an approximately coplanar set of four points from the source cloud.

Parameters

[out]	base_indices	selected source cloud indices, further used as base (B)
[out]	ratio	the two diagonal intersection ratios (r1,r2) of the base points

Returns

< 0 no coplanar four point sets with large enough sampling distance was found
= 0 a set of four congruent points was selected

Definition at line 342 of file ia_fpcs.hpp.

◆ selectBaseTriangle()

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::selectBaseTriangle ( std::vector< int > & base_indices )

protected

Select randomly a triplet of points with large point-to-point distances.

The minimum point sampling distance is calculated based on the estimated point cloud overlap during initialization.

Parameters

[out] base_indices indices of base B

Returns

< 0 no triangle with large enough base lines could be selected
= 0 base triangle succesully selected

Definition at line 408 of file ia_fpcs.hpp.

◆ setApproxOverlap()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setApproxOverlap ( float approx_overlap )

inline

Set the approximate overlap between source and target.

Parameters

[in] approx_overlap the estimated overlap

Definition at line 201 of file ia_fpcs.h.

◆ setDelta()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setDelta	(	float	delta,
		bool	normalize = `false`
	)

inline

Set the constant factor delta which weights the internally calculated parameters.

Parameters

[in]	delta	the weight factor delta
[in]	normalize	flag if delta should be normalized according to point cloud density

Definition at line 183 of file ia_fpcs.h.

◆ setMaxComputationTime()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setMaxComputationTime ( int max_runtime )

inline

Set the maximum computation time in seconds.

Parameters

[in] max_runtime the maximum runtime of the method in seconds

Definition at line 266 of file ia_fpcs.h.

◆ setMaxNormalDifference()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setMaxNormalDifference ( float max_norm_diff )

inline

Set the maximum normal difference between valid point correspondences in degree.

Parameters

[in] max_norm_diff the maximum difference in degree

Definition at line 249 of file ia_fpcs.h.

◆ setNumberOfSamples()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setNumberOfSamples ( int nr_samples )

inline

Set the number of source samples to use during alignment.

Parameters

[in] nr_samples the number of source samples

Definition at line 233 of file ia_fpcs.h.

◆ setNumberOfThreads()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setNumberOfThreads ( int nr_threads )

inline

Set the number of used threads if OpenMP is activated.

Parameters

[in] nr_threads the number of used threads

Definition at line 166 of file ia_fpcs.h.

◆ setScoreThreshold()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setScoreThreshold ( float score_threshold )

inline

Set the scoring threshold used for early finishing the method.

Parameters

[in] score_threshold early terminating score criteria

Definition at line 217 of file ia_fpcs.h.

◆ setSourceNormals()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setSourceNormals ( const NormalsConstPtr & source_normals )

inline

Provide a pointer to the normals of the source point cloud.

Parameters

[in] source_normals pointer to the normals of the source pointer cloud.

Definition at line 134 of file ia_fpcs.h.

◆ setTargetIndices()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setTargetIndices ( const IndicesPtr & target_indices )

inline

Provide a pointer to the vector of target indices.

Parameters

[in] target_indices a pointer to the target indices

Definition at line 118 of file ia_fpcs.h.

◆ setTargetNormals()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setTargetNormals ( const NormalsConstPtr & target_normals )

inline

Provide a pointer to the normals of the target point cloud.

Parameters

[in] target_normals point to the normals of the target point cloud.

Definition at line 150 of file ia_fpcs.h.

◆ setupBase()

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

void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setupBase	(	std::vector< int > &	base_indices,
		float(&)	ratio[2]
	)

protected

Setup the base (four coplanar points) by ordering the points and computing intersection ratios and segment to segment distances of base diagonal.

Parameters

[in,out]	base_indices	indices of base B (will be reordered)
[out]	ratio	diagonal intersection ratios of base points

Definition at line 446 of file ia_fpcs.hpp.

◆ validateMatch()

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateMatch	(	const std::vector< int > &	base_indices,
		const std::vector< int > &	match_indices,
		const pcl::Correspondences &	correspondences,
		Eigen::Matrix4f &	transformation
	)

protectedvirtual

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.

The MSE limit was calculated during initialization (max_mse_).

Parameters

[in]	base_indices	indices of base B
[in]	match_indices	indices of match M
[in]	correspondences	corresondences between source and target
[out]	transformation	resulting transformation matrix

Returns

< 0 MSE bigger than max_mse_
= 0 MSE smaller than max_mse_

Definition at line 829 of file ia_fpcs.hpp.

◆ validateTransformation()

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

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

protectedvirtual

Validate the transformation by calculating the number of inliers after transforming the source cloud.

The resulting fitness 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 fitness_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 in pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >.

Definition at line 861 of file ia_fpcs.hpp.

Member Data Documentation

◆ approx_overlap_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::approx_overlap_

protected

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

Definition at line 476 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getApproxOverlap(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setApproxOverlap().

◆ coincidation_limit_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::coincidation_limit_

protected

Maximal distance between coinciding intersection points to find valid matches.

Note: Internally calculated using an estimation of the point density.

Definition at line 542 of file ia_fpcs.h.

◆ delta_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::delta_

protected

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

It can be used as:

absolute value (normalization = false), value should represent the point accuracy to ensure finding neighbors between source <-> target
relative value (normalization = true), to adjust the internally calculated point accuracy (= point density)

Definition at line 485 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getDelta(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setDelta().

◆ diameter_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::diameter_

protected

Estimated diamter of the target point cloud.

Definition at line 508 of file ia_fpcs.h.

◆ fitness_score_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::fitness_score_

protected

Resulting fitness score of the best match.

Definition at line 505 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getFitnessScore().

◆ max_base_diameter_sqr_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_base_diameter_sqr_

protected

Estimated squared metric overlap between source and target.

Note: Internally calculated using the estimated overlap and the extent of the source cloud. It is used to derive the minimum sampling distance of the base points as well as to calculated the number of tries to reliably find a correct match.

Definition at line 515 of file ia_fpcs.h.

◆ max_edge_diff_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_edge_diff_

protected

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

Note: Internally calculated using an estimation of the point density.

Definition at line 537 of file ia_fpcs.h.

◆ max_inlier_dist_sqr_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_inlier_dist_sqr_

protected

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

Note: Internally calculated using an estimation of the point density.

Definition at line 552 of file ia_fpcs.h.

◆ max_mse_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_mse_

protected

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

Note: Internally calculated using an estimation of the point density.

Definition at line 547 of file ia_fpcs.h.

◆ max_norm_diff_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_norm_diff_

protected

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

Definition at line 498 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getMaxNormalDifference(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setMaxNormalDifference().

◆ max_pair_diff_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_pair_diff_

protected

Maximal difference between corresponding point pairs in source and target.

Note: Internally calculated using an estimation of the point density.

Definition at line 532 of file ia_fpcs.h.

◆ max_runtime_

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_runtime_

protected

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

Definition at line 502 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getMaxComputationTime(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setMaxComputationTime().

◆ normalize_delta_

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

bool pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::normalize_delta_

protected

Normalize delta flag.

Definition at line 521 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setDelta().

◆ nr_samples_

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::nr_samples_

protected

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

(standard = 0 => full cloud).

Definition at line 494 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getNumberOfSamples(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setNumberOfSamples().

◆ nr_threads_

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

int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::nr_threads_

protected

Number of threads for parallelization (standard = 1).

Note: Only used if run compiled with OpenMP.

Definition at line 473 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getNumberOfThreads(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setNumberOfThreads().

◆ score_threshold_

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

float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::score_threshold_

protected

Score threshold to stop calculation with success.

If not set by the user it depends on the size of the approximated overlap

Definition at line 490 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getScoreThreshold(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setScoreThreshold().

◆ small_error_

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

const float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::small_error_

protected

Definition of a small error.

Definition at line 555 of file ia_fpcs.h.

◆ source_indices_

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

pcl::IndicesPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::source_indices_

protected

A pointer to the vector of source point indices to use after sampling.

Definition at line 524 of file ia_fpcs.h.

◆ source_normals_

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

NormalsConstPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::source_normals_

protected

Normals of source point cloud.

Definition at line 465 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getSourceNormals(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setSourceNormals().

◆ target_indices_

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

pcl::IndicesPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::target_indices_

protected

A pointer to the vector of target point indices to use after sampling.

Definition at line 527 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getTargetIndices(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setTargetIndices().

◆ target_normals_

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

NormalsConstPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::target_normals_

protected

Normals of target point cloud.

Definition at line 468 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getTargetNormals(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setTargetNormals().

◆ use_normals_

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

bool pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::use_normals_

protected

Use normals flag.

Definition at line 518 of file ia_fpcs.h.

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

pcl/registration/ia_fpcs.h
pcl/registration/impl/ia_fpcs.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::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >

Constructor & Destructor Documentation

◆ FPCSInitialAlignment()

◆ ~FPCSInitialAlignment()

Member Function Documentation

◆ bruteForceCorrespondences()

◆ checkBaseMatch()

◆ computeTransformation()

◆ determineBaseMatches()

◆ finalCompute()

◆ getApproxOverlap()

◆ getDelta()

◆ getFitnessScore()

◆ getMaxComputationTime()

◆ getMaxNormalDifference()

◆ getNumberOfSamples()

◆ getNumberOfThreads()

◆ getScoreThreshold()

◆ getSourceNormals()

◆ getTargetIndices()

◆ getTargetNormals()

◆ handleMatches()

◆ initCompute()

◆ linkMatchWithBase()

◆ segmentToSegmentDist()

◆ selectBase()

◆ selectBaseTriangle()

◆ setApproxOverlap()

◆ setDelta()

◆ setMaxComputationTime()

◆ setMaxNormalDifference()

◆ setNumberOfSamples()

◆ setNumberOfThreads()

◆ setScoreThreshold()

◆ setSourceNormals()

◆ setTargetIndices()

◆ setTargetNormals()

◆ setupBase()

◆ validateMatch()

◆ validateTransformation()

Member Data Documentation

◆ approx_overlap_

◆ coincidation_limit_

◆ delta_

◆ diameter_

◆ fitness_score_

◆ max_base_diameter_sqr_

◆ max_edge_diff_

◆ max_inlier_dist_sqr_

◆ max_mse_

◆ max_norm_diff_

◆ max_pair_diff_

◆ max_runtime_

◆ normalize_delta_

◆ nr_samples_

◆ nr_threads_

◆ score_threshold_

◆ small_error_

◆ source_indices_

◆ source_normals_

◆ target_indices_

◆ target_normals_

◆ use_normals_

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