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

SampleConsensusInitialAlignment is an implementation of the initial alignment algorithm described in section IV of "Fast Point Feature Histograms (FPFH) for 3D Registration," Rusu et al. More...

#include <pcl/registration/ia_ransac.h>

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List of all members.

Classes

class  ErrorFunctor
class  HuberPenalty
class  TruncatedError

Public Types

typedef Registration
< PointSource, PointTarget >
::PointCloudSource 
PointCloudSource
typedef PointCloudSource::Ptr PointCloudSourcePtr
typedef PointCloudSource::ConstPtr PointCloudSourceConstPtr
typedef Registration
< PointSource, PointTarget >
::PointCloudTarget 
PointCloudTarget
typedef PointIndices::Ptr PointIndicesPtr
typedef PointIndices::ConstPtr PointIndicesConstPtr
typedef pcl::PointCloud< FeatureT > FeatureCloud
typedef FeatureCloud::Ptr FeatureCloudPtr
typedef FeatureCloud::ConstPtr FeatureCloudConstPtr
typedef KdTreeFLANN< FeatureT >
::Ptr 
FeatureKdTreePtr
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 PointCloudTarget::Ptr PointCloudTargetPtr
typedef PointCloudTarget::ConstPtr PointCloudTargetConstPtr
typedef
KdTree::PointRepresentationConstPtr 
PointRepresentationConstPtr
typedef
pcl::registration::TransformationEstimation
< PointSource, PointTarget > 
TransformationEstimation
typedef
TransformationEstimation::Ptr 
TransformationEstimationPtr
typedef
TransformationEstimation::ConstPtr 
TransformationEstimationConstPtr

Public Member Functions

 SampleConsensusInitialAlignment ()
 Constructor.
void setSourceFeatures (const FeatureCloudConstPtr &features)
 Provide a boost shared pointer to the source point cloud's feature descriptors.
FeatureCloudConstPtr const getSourceFeatures ()
 Get a pointer to the source point cloud's features.
void setTargetFeatures (const FeatureCloudConstPtr &features)
 Provide a boost shared pointer to the target point cloud's feature descriptors.
FeatureCloudConstPtr const getTargetFeatures ()
 Get a pointer to the target point cloud's features.
void setMinSampleDistance (float min_sample_distance)
 Set the minimum distances between samples.
float getMinSampleDistance ()
 Get the minimum distances between samples, as set by the user.
void setNumberOfSamples (int nr_samples)
 Set the number of samples to use during each iteration.
int getNumberOfSamples ()
 Get the number of samples to use during each iteration, as set by the user.
void setCorrespondenceRandomness (int k)
 Set the number of neighbors to use when selecting a random feature correspondence.
int getCorrespondenceRandomness ()
 Get the number of neighbors used when selecting a random feature correspondence, as set by the user.
void setErrorFunction (const boost::shared_ptr< ErrorFunctor > &error_functor)
 Specify the error function to minimize.
boost::shared_ptr< ErrorFunctorgetErrorFunction ()
 Get a shared pointer to the ErrorFunctor that is to be minimized.
void setTransformationEstimation (const TransformationEstimationPtr &te)
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)
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

SampleConsensusInitialAlignment is an implementation of the initial alignment algorithm described in section IV of "Fast Point Feature Histograms (FPFH) for 3D Registration," Rusu et al.

Author:
Radu Bogdan Rusu, Michael Dixon

Member Typedef Documentation

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

Definition at line 70 of file registration.h.

Definition at line 78 of file ia_ransac.h.

Definition at line 80 of file ia_ransac.h.

Definition at line 79 of file ia_ransac.h.

Definition at line 123 of file ia_ransac.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 69 of file ia_ransac.h.

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

Definition at line 71 of file ia_ransac.h.

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

Definition at line 70 of file ia_ransac.h.

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

Definition at line 73 of file ia_ransac.h.

typedef PointCloudTarget::ConstPtr pcl::Registration::PointCloudTargetConstPtr [inherited]

Reimplemented in pcl::PPFRegistration.

Definition at line 81 of file registration.h.

typedef PointCloudTarget::Ptr pcl::Registration::PointCloudTargetPtr [inherited]

Reimplemented in pcl::PPFRegistration.

Definition at line 80 of file registration.h.

Definition at line 76 of file ia_ransac.h.

Definition at line 75 of file ia_ransac.h.

Definition at line 83 of file 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::SampleConsensusInitialAlignment::SampleConsensusInitialAlignment ( ) [inline]

Constructor.

Definition at line 125 of file ia_ransac.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.

int pcl::SampleConsensusInitialAlignment::getCorrespondenceRandomness ( ) [inline]

Get the number of neighbors used when selecting a random feature correspondence, as set by the user.

Definition at line 182 of file ia_ransac.h.

boost::shared_ptr<ErrorFunctor> pcl::SampleConsensusInitialAlignment::getErrorFunction ( ) [inline]

Get a shared pointer to the ErrorFunctor that is to be minimized.

Returns:
A shared pointer to a subclass of SampleConsensusInitialAlignment::ErrorFunctor

Definition at line 195 of file ia_ransac.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::SampleConsensusInitialAlignment::getMinSampleDistance ( ) [inline]

Get the minimum distances between samples, as set by the user.

Definition at line 161 of file ia_ransac.h.

int pcl::SampleConsensusInitialAlignment::getNumberOfSamples ( ) [inline]

Get the number of samples to use during each iteration, as set by the user.

Definition at line 171 of file ia_ransac.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.

FeatureCloudConstPtr const pcl::SampleConsensusInitialAlignment::getSourceFeatures ( ) [inline]

Get a pointer to the source point cloud's features.

Definition at line 141 of file ia_ransac.h.

FeatureCloudConstPtr const pcl::SampleConsensusInitialAlignment::getTargetFeatures ( ) [inline]

Get a pointer to the target point cloud's features.

Definition at line 151 of file ia_ransac.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::SampleConsensusInitialAlignment::setCorrespondenceRandomness ( int  k) [inline]

Set the number of neighbors to use when selecting a random feature correspondence.

A higher value will add more randomness to the feature matching.

Parameters:
kthe number of neighbors to use when selecting a random feature correspondence.

Definition at line 178 of file ia_ransac.h.

void pcl::SampleConsensusInitialAlignment::setErrorFunction ( const boost::shared_ptr< ErrorFunctor > &  error_functor) [inline]

Specify the error function to minimize.

Note:
This call is optional. TruncatedError will be used by default
Parameters:
Ashared pointer to a subclass of SampleConsensusInitialAlignment::ErrorFunctor

Definition at line 189 of file ia_ransac.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.

virtual void pcl::Registration::setInputTarget ( const PointCloudTargetConstPtr cloud) [inline, virtual, inherited]

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 in pcl::PPFRegistration, and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >.

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::SampleConsensusInitialAlignment::setMinSampleDistance ( float  min_sample_distance) [inline]

Set the minimum distances between samples.

Parameters:
min_sample_distancethe minimum distances between samples

Definition at line 157 of file ia_ransac.h.

void pcl::SampleConsensusInitialAlignment::setNumberOfSamples ( int  nr_samples) [inline]

Set the number of samples to use during each iteration.

Parameters:
nr_samplesthe number of samples to use during each iteration

Definition at line 167 of file ia_ransac.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::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::SampleConsensusInitialAlignment::setSourceFeatures ( const FeatureCloudConstPtr features)

Provide a boost shared pointer to the source point cloud's feature descriptors.

Parameters:
featuresthe source point cloud's features

Definition at line 40 of file ia_ransac.hpp.

void pcl::SampleConsensusInitialAlignment::setTargetFeatures ( const FeatureCloudConstPtr features)

Provide a boost shared pointer to the target point cloud's feature descriptors.

Parameters:
featuresthe target point cloud's features

Definition at line 52 of file ia_ransac.hpp.

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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