Point Cloud Library (PCL)  1.3.1
Classes | Public Types | Public Member Functions
pcl::PPFRegistration Class Reference

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

#include <pcl/registration/ppf_registration.h>

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List of all members.

Classes

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

Public Types

typedef std::vector
< PoseWithVotes,
Eigen::aligned_allocator
< PoseWithVotes > > 
PoseWithVotesList
typedef pcl::PointCloud
< PointSource > 
PointCloudSource
typedef PointCloudSource::Ptr PointCloudSourcePtr
typedef PointCloudSource::ConstPtr PointCloudSourceConstPtr
typedef pcl::PointCloud
< PointTarget > 
PointCloudTarget
typedef PointCloudTarget::Ptr PointCloudTargetPtr
typedef PointCloudTarget::ConstPtr PointCloudTargetConstPtr
typedef boost::shared_ptr
< Registration< PointSource,
PointTarget > > 
Ptr
typedef boost::shared_ptr
< const Registration
< PointSource, PointTarget > > 
ConstPtr
typedef pcl::KdTree< PointTarget > KdTree
typedef pcl::KdTree
< PointTarget >::Ptr 
KdTreePtr
typedef
KdTree::PointRepresentationConstPtr 
PointRepresentationConstPtr
typedef
pcl::registration::TransformationEstimation
< PointSource, PointTarget > 
TransformationEstimation
typedef
TransformationEstimation::Ptr 
TransformationEstimationPtr
typedef
TransformationEstimation::ConstPtr 
TransformationEstimationConstPtr

Public Member Functions

 PPFRegistration ()
 Empty constructor that initializes all the parameters of the algorithm with default values.
void setPositionClusteringThreshold (float clustering_position_diff_threshold)
 Method for setting the position difference clustering parameter.
float getPositionClusteringThreshold ()
 Returns the parameter defining the position difference clustering parameter - distance threshold below which two poses are considered close enough to be in the same cluster (for the clustering phase of the algorithm)
void setRotationClusteringThreshold (float clustering_rotation_diff_threshold)
 Method for setting the rotation clustering parameter.
float getRotationClusteringThreshold ()
 Returns the parameter defining the rotation clustering threshold.
void setSceneReferencePointSamplingRate (unsigned int scene_reference_point_sampling_rate)
 Method for setting the scene reference point sampling rate.
unsigned int getSceneReferencePointSamplingRate ()
 Returns the parameter for the scene reference point sampling rate of the algorithm.
void setSearchMethod (PPFHashMapSearch::Ptr search_method)
 Function that sets the search method for the algorithm.
PPFHashMapSearch::Ptr getSearchMethod ()
 Getter function for the search method of the class.
void setInputTarget (const PointCloudTargetConstPtr &cloud)
 Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to)
void setTransformationEstimation (const TransformationEstimationPtr &te)
PointCloudTargetConstPtr const getInputTarget ()
 Get a pointer to the input point cloud dataset target.
Eigen::Matrix4f getFinalTransformation ()
 Get the final transformation matrix estimated by the registration method.
Eigen::Matrix4f getLastIncrementalTransformation ()
 Get the last incremental transformation matrix estimated by the registration method.
void setMaximumIterations (int nr_iterations)
 Set the maximum number of iterations the internal optimization should run for.
int getMaximumIterations ()
 Get the maximum number of iterations the internal optimization should run for, as set by the user.
void setRANSACOutlierRejectionThreshold (double inlier_threshold)
 Set the inlier distance threshold for the internal RANSAC outlier rejection loop.
double getRANSACOutlierRejectionThreshold ()
 Get the inlier distance threshold for the internal outlier rejection loop as set by the user.
void setMaxCorrespondenceDistance (double distance_threshold)
 Set the maximum distance threshold between two correspondent points in source <-> target.
double getMaxCorrespondenceDistance ()
 Get the maximum distance threshold between two correspondent points in source <-> target.
void setTransformationEpsilon (double epsilon)
 Set the transformation epsilon (maximum allowable difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution.
double getTransformationEpsilon ()
 Get the transformation epsilon (maximum allowable difference between two consecutive transformations) as set by the user.
void setEuclideanFitnessEpsilon (double epsilon)
 Set the maximum allowed Euclidean error between two consecutive steps in the ICP loop, before the algorithm is considered to have converged.
double getEuclideanFitnessEpsilon ()
 Get the maximum allowed distance error before the algorithm will be considered to have converged, as set by the user.
void setPointRepresentation (const PointRepresentationConstPtr &point_representation)
 Provide a boost shared pointer to the PointRepresentation to be used when comparing points.
bool registerVisualizationCallback (boost::function< FunctionSignature > &visualizerCallback)
 Register the user callback function which will be called from registration thread in order to update point cloud obtained after each iteration.
double getFitnessScore (double max_range=std::numeric_limits< double >::max())
 Obtain the Euclidean fitness score (e.g., sum of squared distances from the source to the target)
double getFitnessScore (const std::vector< float > &distances_a, const std::vector< float > &distances_b)
 Obtain the Euclidean fitness score (e.g., sum of squared distances from the source to the target) from two sets of correspondence distances (distances between source and target points)
bool hasConverged ()
 Return the state of convergence after the last align run.
void align (PointCloudSource &output)
 Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output.
void align (PointCloudSource &output, const Eigen::Matrix4f &guess)
 Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output.
const std::string & getClassName () const
 Abstract class get name method.

Detailed Description

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

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

Note:
This class works in tandem with the PPFEstimation class
Author:
Alexandru-Eugen Ichim

Member Typedef Documentation

typedef boost::shared_ptr< const Registration<PointSource, PointTarget> > pcl::Registration::ConstPtr [inherited]

Definition at line 70 of file registration.h.

typedef pcl::KdTree<PointTarget> pcl::Registration::KdTree [inherited]

Definition at line 72 of file registration.h.

typedef pcl::KdTree<PointTarget>::Ptr pcl::Registration::KdTreePtr [inherited]

Definition at line 73 of file registration.h.

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

Definition at line 167 of file ppf_registration.h.

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

Definition at line 169 of file ppf_registration.h.

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

Definition at line 168 of file ppf_registration.h.

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

Definition at line 171 of file ppf_registration.h.

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

Definition at line 173 of file ppf_registration.h.

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

Definition at line 172 of file ppf_registration.h.

Definition at line 83 of file registration.h.

typedef std::vector<PoseWithVotes, Eigen::aligned_allocator<PoseWithVotes> > pcl::PPFRegistration::PoseWithVotesList

Definition at line 157 of file ppf_registration.h.

typedef boost::shared_ptr< Registration<PointSource, PointTarget> > pcl::Registration::Ptr [inherited]

Definition at line 69 of file registration.h.

Definition at line 85 of file registration.h.

Definition at line 87 of file registration.h.

Definition at line 86 of file registration.h.


Constructor & Destructor Documentation

pcl::PPFRegistration::PPFRegistration ( ) [inline]

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

Definition at line 177 of file ppf_registration.h.


Member Function Documentation

void pcl::Registration::align ( PointCloudSource output) [inline, inherited]

Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output.

Parameters:
outputthe resultant input transfomed point cloud dataset
void pcl::Registration::align ( PointCloudSource output,
const Eigen::Matrix4f &  guess 
) [inline, inherited]

Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output.

Parameters:
outputthe resultant input transfomed point cloud dataset
guessthe initial gross estimation of the transformation
const std::string& pcl::Registration::getClassName ( ) const [inline, inherited]

Abstract class get name method.

Definition at line 263 of file registration.h.

double pcl::Registration::getEuclideanFitnessEpsilon ( ) [inline, inherited]

Get the maximum allowed distance error before the algorithm will be considered to have converged, as set by the user.

See setEuclideanFitnessEpsilon

Definition at line 200 of file registration.h.

Eigen::Matrix4f pcl::Registration::getFinalTransformation ( ) [inline, inherited]

Get the final transformation matrix estimated by the registration method.

Definition at line 126 of file registration.h.

double pcl::Registration::getFitnessScore ( double  max_range = std::numeric_limits<double>::max ()) [inline, inherited]

Obtain the Euclidean fitness score (e.g., sum of squared distances from the source to the target)

Parameters:
max_rangemaximum allowable distance between a point and its correspondence in the target (default: double::max)
double pcl::Registration::getFitnessScore ( const std::vector< float > &  distances_a,
const std::vector< float > &  distances_b 
) [inline, inherited]

Obtain the Euclidean fitness score (e.g., sum of squared distances from the source to the target) from two sets of correspondence distances (distances between source and target points)

Parameters:
[in]distances_athe first set of distances between correspondences
[in]distances_bthe second set of distances between correspondences
PointCloudTargetConstPtr const pcl::Registration::getInputTarget ( ) [inline, inherited]

Get a pointer to the input point cloud dataset target.

Definition at line 122 of file registration.h.

Eigen::Matrix4f pcl::Registration::getLastIncrementalTransformation ( ) [inline, inherited]

Get the last incremental transformation matrix estimated by the registration method.

Definition at line 130 of file registration.h.

double pcl::Registration::getMaxCorrespondenceDistance ( ) [inline, inherited]

Get the maximum distance threshold between two correspondent points in source <-> target.

If the distance is larger than this threshold, the points will be ignored in the alignment process.

Definition at line 168 of file registration.h.

int pcl::Registration::getMaximumIterations ( ) [inline, inherited]

Get the maximum number of iterations the internal optimization should run for, as set by the user.

Definition at line 140 of file registration.h.

float pcl::PPFRegistration::getPositionClusteringThreshold ( ) [inline]

Returns the parameter defining the position difference clustering parameter - distance threshold below which two poses are considered close enough to be in the same cluster (for the clustering phase of the algorithm)

Definition at line 197 of file ppf_registration.h.

double pcl::Registration::getRANSACOutlierRejectionThreshold ( ) [inline, inherited]

Get the inlier distance threshold for the internal outlier rejection loop as set by the user.

Definition at line 154 of file registration.h.

float pcl::PPFRegistration::getRotationClusteringThreshold ( ) [inline]

Returns the parameter defining the rotation clustering threshold.

Definition at line 209 of file ppf_registration.h.

unsigned int pcl::PPFRegistration::getSceneReferencePointSamplingRate ( ) [inline]

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

Definition at line 219 of file ppf_registration.h.

PPFHashMapSearch::Ptr pcl::PPFRegistration::getSearchMethod ( ) [inline]

Getter function for the search method of the class.

Definition at line 231 of file ppf_registration.h.

double pcl::Registration::getTransformationEpsilon ( ) [inline, inherited]

Get the transformation epsilon (maximum allowable difference between two consecutive transformations) as set by the user.

Definition at line 183 of file registration.h.

bool pcl::Registration::hasConverged ( ) [inline, inherited]

Return the state of convergence after the last align run.

Definition at line 244 of file registration.h.

bool pcl::Registration::registerVisualizationCallback ( boost::function< FunctionSignature > &  visualizerCallback) [inline, inherited]

Register the user callback function which will be called from registration thread in order to update point cloud obtained after each iteration.

Parameters:
refferenceof the user callback function

Definition at line 216 of file registration.h.

void pcl::Registration::setEuclideanFitnessEpsilon ( double  epsilon) [inline, inherited]

Set the maximum allowed Euclidean error between two consecutive steps in the ICP loop, before the algorithm is considered to have converged.

The error is estimated as the sum of the differences between correspondences in an Euclidean sense, divided by the number of correspondences.

Parameters:
epsilonthe maximum allowed distance error before the algorithm will be considered to have converged

Definition at line 194 of file registration.h.

void pcl::PPFRegistration::setInputTarget ( const PointCloudTargetConstPtr cloud) [virtual]

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

Parameters:
cloudthe input point cloud target

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

Definition at line 106 of file ppf_registration.hpp.

void pcl::Registration::setMaxCorrespondenceDistance ( double  distance_threshold) [inline, inherited]

Set the maximum distance threshold between two correspondent points in source <-> target.

If the distance is larger than this threshold, the points will be ignored in the alignment process.

Parameters:
distance_thresholdthe maximum distance threshold between a point and its nearest neighbor correspondent in order to be considered in the alignment process

Definition at line 162 of file registration.h.

void pcl::Registration::setMaximumIterations ( int  nr_iterations) [inline, inherited]

Set the maximum number of iterations the internal optimization should run for.

Parameters:
nr_iterationsthe maximum number of iterations the internal optimization should run for

Definition at line 136 of file registration.h.

void pcl::Registration::setPointRepresentation ( const PointRepresentationConstPtr point_representation) [inline, inherited]

Provide a boost shared pointer to the PointRepresentation to be used when comparing points.

Parameters:
point_representationthe PointRepresentation to be used by the k-D tree

Definition at line 206 of file registration.h.

void pcl::PPFRegistration::setPositionClusteringThreshold ( float  clustering_position_diff_threshold) [inline]

Method for setting the position difference clustering parameter.

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

Definition at line 190 of file ppf_registration.h.

void pcl::Registration::setRANSACOutlierRejectionThreshold ( double  inlier_threshold) [inline, inherited]

Set the inlier distance threshold for the internal RANSAC outlier rejection loop.

The method considers a point to be an inlier, if the distance between the target data index and the transformed source index is smaller than the given inlier distance threshold. The value is set by default to 0.05m.

Parameters:
inlier_thresholdthe inlier distance threshold for the internal RANSAC outlier rejection loop

Definition at line 150 of file registration.h.

void pcl::PPFRegistration::setRotationClusteringThreshold ( float  clustering_rotation_diff_threshold) [inline]

Method for setting the rotation clustering parameter.

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

Definition at line 204 of file ppf_registration.h.

void pcl::PPFRegistration::setSceneReferencePointSamplingRate ( unsigned int  scene_reference_point_sampling_rate) [inline]

Method for setting the scene reference point sampling rate.

Parameters:
scene_reference_point_sampling_ratesampling rate for the scene reference point

Definition at line 215 of file ppf_registration.h.

void pcl::PPFRegistration::setSearchMethod ( PPFHashMapSearch::Ptr  search_method) [inline]

Function that sets the search method for the algorithm.

Note:
Right now, the only available method is the one initially proposed by the authors - by using a hash map with discretized feature vectors
Parameters:
search_methodsmart pointer to the search method to be set

Definition at line 227 of file ppf_registration.h.

void pcl::Registration::setTransformationEpsilon ( double  epsilon) [inline, inherited]

Set the transformation epsilon (maximum allowable difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution.

Parameters:
epsilonthe transformation epsilon in order for an optimization to be considered as having converged to the final solution.

Definition at line 177 of file registration.h.

void pcl::Registration::setTransformationEstimation ( const TransformationEstimationPtr te) [inline, inherited]

Definition at line 112 of file registration.h.


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