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GeneralizedIterativeClosestPoint6D integrates L*a*b* color space information into the Generalized Iterative Closest Point (GICP) algorithm. More...

#include <pcl/registration/gicp6d.h>

Classes
class	MyPointRepresentation
	Custom point representation to perform kdtree searches in more than 3 (i.e. More...

Public Member Functions
	GeneralizedIterativeClosestPoint6D (float lab_weight=0.032f)
	constructor. More...

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

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

Public Member Functions inherited from pcl::GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >
	GeneralizedIterativeClosestPoint ()
	Empty constructor. More...

void	setInputSource (const PointCloudSourceConstPtr &cloud) override
	Provide a pointer to the input dataset. More...

void	setSourceCovariances (const MatricesVectorPtr &covariances)
	Provide a pointer to the covariances of the input source (if computed externally!). More...

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

void	setTargetCovariances (const MatricesVectorPtr &covariances)
	Provide a pointer to the covariances of the input target (if computed externally!). More...

void	estimateRigidTransformationBFGS (const PointCloudSource &cloud_src, const pcl::Indices &indices_src, const PointCloudTarget &cloud_tgt, const pcl::Indices &indices_tgt, Eigen::Matrix4f &transformation_matrix)
	Estimate a rigid rotation transformation between a source and a target point cloud using an iterative non-linear Levenberg-Marquardt approach. More...

const Eigen::Matrix3d &	mahalanobis (std::size_t index) const

void	computeRDerivative (const Vector6d &x, const Eigen::Matrix3d &R, Vector6d &g) const
	Computes rotation matrix derivative. More...

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

double	getRotationEpsilon () const
	Get the rotation epsilon (maximum allowable difference between two consecutive rotations) as set by the user. More...

void	setCorrespondenceRandomness (int k)
	Set the number of neighbors used when selecting a point neighbourhood to compute covariances. More...

int	getCorrespondenceRandomness () const
	Get the number of neighbors used when computing covariances as set by the user. More...

void	setMaximumOptimizerIterations (int max)
	Set maximum number of iterations at the optimization step. More...

int	getMaximumOptimizerIterations () const
	Return maximum number of iterations at the optimization step. More...

void	setTranslationGradientTolerance (double tolerance)
	Set the minimal translation gradient threshold for early optimization stop. More...

double	getTranslationGradientTolerance () const
	Return the minimal translation gradient threshold for early optimization stop. More...

void	setRotationGradientTolerance (double tolerance)
	Set the minimal rotation gradient threshold for early optimization stop. More...

double	getRotationGradientTolerance () const
	Return the minimal rotation gradient threshold for early optimization stop. More...

Public Member Functions inherited from pcl::IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >
	IterativeClosestPoint ()
	Empty constructor. More...

	IterativeClosestPoint (const IterativeClosestPoint &)=delete
	Due to `convergence_criteria_` holding references to the class members, it is tricky to correctly implement its copy and move operations correctly. More...

	IterativeClosestPoint (IterativeClosestPoint &&)=delete

IterativeClosestPoint &	operator= (const IterativeClosestPoint &)=delete

IterativeClosestPoint &	operator= (IterativeClosestPoint &&)=delete

	~IterativeClosestPoint ()
	Empty destructor. More...

pcl::registration::DefaultConvergenceCriteria< float >::Ptr	getConvergeCriteria ()
	Returns a pointer to the DefaultConvergenceCriteria used by the IterativeClosestPoint class. More...

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

void	setInputTarget (const PointCloudTargetConstPtr &cloud) override
	Provide a pointer to the input target (e.g., the point cloud that we want to align to the target) More...

void	setUseReciprocalCorrespondences (bool use_reciprocal_correspondence)
	Set whether to use reciprocal correspondence or not. More...

bool	getUseReciprocalCorrespondences () const
	Obtain whether reciprocal correspondence are used or not. More...

Public Member Functions inherited from pcl::Registration< PointXYZRGBA, PointXYZRGBA, 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...

const PointCloudSourceConstPtr	getInputSource ()
	Get a pointer to the input point cloud dataset target. 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< PointXYZRGBA >
	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 PointXYZRGBA &	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 with initial guess. More...

bool	searchForNeighbors (const PointXYZLAB &query, pcl::Indices &index, std::vector< float > &distance)
	Search for the closest nearest neighbor of a given point. More...

Protected Member Functions inherited from pcl::GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >
void	computeCovariances (typename pcl::PointCloud< PointT >::ConstPtr cloud, const typename pcl::search::KdTree< PointT >::Ptr tree, MatricesVector &cloud_covariances)
	compute points covariances matrices according to the K nearest neighbors. More...

double	matricesInnerProd (const Eigen::MatrixXd &mat1, const Eigen::MatrixXd &mat2) const

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

bool	searchForNeighbors (const PointXYZRGBA &query, pcl::Indices &index, std::vector< float > &distance)
	Search for the closest nearest neighbor of a given point. More...

void	applyState (Eigen::Matrix4f &t, const Vector6d &x) const
	compute transformation matrix from transformation matrix More...

Protected Member Functions inherited from pcl::IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >
virtual void	transformCloud (const PointCloudSource &input, PointCloudSource &output, const Matrix4 &transform)
	Apply a rigid transform to a given dataset. More...

void	computeTransformation (PointCloudSource &output, const Matrix4 &guess) override
	Rigid transformation computation method with initial guess. More...

virtual void	determineRequiredBlobData ()
	Looks at the Estimators and Rejectors and determines whether their blob-setter methods need to be called. More...

Protected Member Functions inherited from pcl::Registration< PointXYZRGBA, PointXYZRGBA, 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< PointXYZRGBA >
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
pcl::PointCloud< PointXYZLAB >::Ptr	cloud_lab_
	Holds the converted (LAB) data cloud. More...

pcl::PointCloud< PointXYZLAB >::Ptr	target_lab_
	Holds the converted (LAB) model cloud. More...

KdTreeFLANN< PointXYZLAB >	target_tree_lab_
	6d-tree to search in model cloud. More...

float	lab_weight_
	The color weight. More...

MyPointRepresentation	point_rep_
	Enables 6d searches with kd-tree class using the color weight. More...

Protected Attributes inherited from pcl::GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >
int	k_correspondences_
	The number of neighbors used for covariances computation. More...

double	gicp_epsilon_
	The epsilon constant for gicp paper; this is NOT the convergence tolerance default: 0.001. More...

double	rotation_epsilon_
	The epsilon constant for rotation error. More...

Eigen::Matrix4f	base_transformation_
	base transformation More...

const PointCloudSource *	tmp_src_
	Temporary pointer to the source dataset. More...

const PointCloudTarget *	tmp_tgt_
	Temporary pointer to the target dataset. More...

const pcl::Indices *	tmp_idx_src_
	Temporary pointer to the source dataset indices. More...

const pcl::Indices *	tmp_idx_tgt_
	Temporary pointer to the target dataset indices. More...

MatricesVectorPtr	input_covariances_
	Input cloud points covariances. More...

MatricesVectorPtr	target_covariances_
	Target cloud points covariances. More...

std::vector< Eigen::Matrix3d >	mahalanobis_
	Mahalanobis matrices holder. More...

int	max_inner_iterations_
	maximum number of optimizations More...

double	translation_gradient_tolerance_
	minimal translation gradient for early optimization stop More...

double	rotation_gradient_tolerance_
	minimal rotation gradient for early optimization stop More...

std::function< void(const pcl::PointCloud< PointXYZRGBA > &cloud_src, const pcl::Indices &src_indices, const pcl::PointCloud< PointXYZRGBA > &cloud_tgt, const pcl::Indices &tgt_indices, Eigen::Matrix4f &transformation_matrix)>	rigid_transformation_estimation_

Protected Attributes inherited from pcl::IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >
std::size_t	x_idx_offset_
	XYZ fields offset. More...

std::size_t	y_idx_offset_

std::size_t	z_idx_offset_

std::size_t	nx_idx_offset_
	Normal fields offset. More...

std::size_t	ny_idx_offset_

std::size_t	nz_idx_offset_

bool	use_reciprocal_correspondence_
	The correspondence type used for correspondence estimation. More...

bool	source_has_normals_
	Internal check whether source dataset has normals or not. More...

bool	target_has_normals_
	Internal check whether target dataset has normals or not. More...

bool	need_source_blob_
	Checks for whether estimators and rejectors need various data. More...

bool	need_target_blob_

Protected Attributes inherited from pcl::Registration< PointXYZRGBA, PointXYZRGBA, 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< PointXYZRGBA >
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::GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >
using	PointCloudSource = pcl::PointCloud< PointXYZRGBA >

using	PointCloudSourcePtr = typename PointCloudSource::Ptr

using	PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr

using	PointCloudTarget = pcl::PointCloud< PointXYZRGBA >

using	PointCloudTargetPtr = typename PointCloudTarget::Ptr

using	PointCloudTargetConstPtr = typename PointCloudTarget::ConstPtr

using	PointIndicesPtr = PointIndices::Ptr

using	PointIndicesConstPtr = PointIndices::ConstPtr

using	MatricesVector = std::vector< Eigen::Matrix3d, Eigen::aligned_allocator< Eigen::Matrix3d > >

using	MatricesVectorPtr = shared_ptr< MatricesVector >

using	MatricesVectorConstPtr = shared_ptr< const MatricesVector >

using	InputKdTree = typename Registration< PointXYZRGBA, PointXYZRGBA >::KdTree

using	InputKdTreePtr = typename Registration< PointXYZRGBA, PointXYZRGBA >::KdTreePtr

using	Ptr = shared_ptr< GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA > >

using	ConstPtr = shared_ptr< const GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA > >

using	Vector6d = Eigen::Matrix< double, 6, 1 >

Public Types inherited from pcl::IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >
using	PointCloudSource = typename Registration< PointXYZRGBA, PointXYZRGBA, float >::PointCloudSource

using	PointCloudSourcePtr = typename PointCloudSource::Ptr

using	PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr

using	PointCloudTarget = typename Registration< PointXYZRGBA, PointXYZRGBA, float >::PointCloudTarget

using	PointCloudTargetPtr = typename PointCloudTarget::Ptr

using	PointCloudTargetConstPtr = typename PointCloudTarget::ConstPtr

using	PointIndicesPtr = PointIndices::Ptr

using	PointIndicesConstPtr = PointIndices::ConstPtr

using	Ptr = shared_ptr< IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA, float > >

using	ConstPtr = shared_ptr< const IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA, float > >

using	Matrix4 = typename Registration< PointXYZRGBA, PointXYZRGBA, float >::Matrix4

Public Types inherited from pcl::Registration< PointXYZRGBA, PointXYZRGBA, float >
using	Matrix4 = Eigen::Matrix< float, 4, 4 >

using	Ptr = shared_ptr< Registration< PointXYZRGBA, PointXYZRGBA, float > >

using	ConstPtr = shared_ptr< const Registration< PointXYZRGBA, PointXYZRGBA, float > >

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

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

using	KdTreePtr = typename KdTree::Ptr

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

using	KdTreeReciprocalPtr = typename KdTreeReciprocal::Ptr

using	PointCloudSource = pcl::PointCloud< PointXYZRGBA >

using	PointCloudSourcePtr = typename PointCloudSource::Ptr

using	PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr

using	PointCloudTarget = pcl::PointCloud< PointXYZRGBA >

using	PointCloudTargetPtr = typename PointCloudTarget::Ptr

using	PointCloudTargetConstPtr = typename PointCloudTarget::ConstPtr

using	PointRepresentationConstPtr = typename KdTree::PointRepresentationConstPtr

using	TransformationEstimation = typename pcl::registration::TransformationEstimation< PointXYZRGBA, PointXYZRGBA, float >

using	TransformationEstimationPtr = typename TransformationEstimation::Ptr

using	TransformationEstimationConstPtr = typename TransformationEstimation::ConstPtr

using	CorrespondenceEstimation = pcl::registration::CorrespondenceEstimationBase< PointXYZRGBA, PointXYZRGBA, float >

using	CorrespondenceEstimationPtr = typename CorrespondenceEstimation::Ptr

using	CorrespondenceEstimationConstPtr = typename CorrespondenceEstimation::ConstPtr

using	UpdateVisualizerCallbackSignature = void(const pcl::PointCloud< PointXYZRGBA > &, const pcl::Indices &, const pcl::PointCloud< PointXYZRGBA > &, 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< PointXYZRGBA >
using	PointCloud = pcl::PointCloud< PointXYZRGBA >

using	PointCloudPtr = typename PointCloud::Ptr

using	PointCloudConstPtr = typename PointCloud::ConstPtr

using	PointIndicesPtr = PointIndices::Ptr

using	PointIndicesConstPtr = PointIndices::ConstPtr

Public Attributes inherited from pcl::IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA >
pcl::registration::DefaultConvergenceCriteria< float >::Ptr	convergence_criteria_

Detailed Description

GeneralizedIterativeClosestPoint6D integrates L*a*b* color space information into the Generalized Iterative Closest Point (GICP) algorithm.

The suggested input is PointXYZRGBA.

Note: If you use this code in any academic work, please cite:

M. Korn, M. Holzkothen, J. Pauli Color Supported Generalized-ICP. In Proceedings of VISAPP 2014 - International Conference on Computer Vision Theory and Applications, Lisbon, Portugal, January 2014.

Author: Martin Holzkothen, Michael Korn

Definition at line 65 of file gicp6d.h.

Constructor & Destructor Documentation

GeneralizedIterativeClosestPoint6D()

pcl::GeneralizedIterativeClosestPoint6D::GeneralizedIterativeClosestPoint6D ( float lab_weight = 0.032f )

constructor.

Parameters

[in] lab_weight the color weight

Member Function Documentation

computeTransformation()

void pcl::GeneralizedIterativeClosestPoint6D::computeTransformation	(	PointCloudSource &	output,
		const Eigen::Matrix4f &	guess
	)

overrideprotected

Rigid transformation computation method with initial guess.

Parameters

output	the transformed input point cloud dataset using the rigid transformation found
guess	the initial guess of the transformation to compute

searchForNeighbors()

bool pcl::GeneralizedIterativeClosestPoint6D::searchForNeighbors	(	const PointXYZLAB &	query,
		pcl::Indices &	index,
		std::vector< float > &	distance
	)

inlineprotected

Search for the closest nearest neighbor of a given point.

Parameters

query	the point to search a nearest neighbour for
index	vector of size 1 to store the index of the nearest neighbour found
distance	vector of size 1 to store the distance to nearest neighbour found

setInputSource()

void pcl::GeneralizedIterativeClosestPoint6D::setInputSource ( const PointCloudSourceConstPtr & cloud )

overridevirtual

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

Parameters

[in] cloud the input point cloud source

Reimplemented from pcl::Registration< PointXYZRGBA, PointXYZRGBA, float >.

setInputTarget()

void pcl::GeneralizedIterativeClosestPoint6D::setInputTarget ( const PointCloudTargetConstPtr & target )

overridevirtual

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

Parameters

[in] target the input point cloud target

Reimplemented from pcl::Registration< PointXYZRGBA, PointXYZRGBA, float >.

Member Data Documentation

cloud_lab_

pcl::PointCloud<PointXYZLAB>::Ptr pcl::GeneralizedIterativeClosestPoint6D::cloud_lab_

protected

Holds the converted (LAB) data cloud.

Definition at line 115 of file gicp6d.h.

lab_weight_

float pcl::GeneralizedIterativeClosestPoint6D::lab_weight_

protected

The color weight.

Definition at line 124 of file gicp6d.h.

point_rep_

MyPointRepresentation pcl::GeneralizedIterativeClosestPoint6D::point_rep_

protected

Enables 6d searches with kd-tree class using the color weight.

Definition at line 164 of file gicp6d.h.

target_lab_

pcl::PointCloud<PointXYZLAB>::Ptr pcl::GeneralizedIterativeClosestPoint6D::target_lab_

protected

Holds the converted (LAB) model cloud.

Definition at line 118 of file gicp6d.h.

target_tree_lab_

KdTreeFLANN<PointXYZLAB> pcl::GeneralizedIterativeClosestPoint6D::target_tree_lab_

protected

6d-tree to search in model cloud.

Definition at line 121 of file gicp6d.h.

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

pcl/registration/gicp6d.h

© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_generalized_iterative_closest_point6_d.html

Classes

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

GeneralizedIterativeClosestPoint6D()

Member Function Documentation

computeTransformation()

searchForNeighbors()

setInputSource()

setInputTarget()

Member Data Documentation

cloud_lab_

lab_weight_

point_rep_

target_lab_

target_tree_lab_