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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:

© 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