Public Member Functions | Protected Member Functions | Protected Attributes

pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT > Class Template Reference
[Module registration]

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>

Inheritance diagram for pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >:
Inheritance graph
[legend]
Collaboration diagram for pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >:
Collaboration graph
[legend]

List of all members.

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 ()
 Set the number of samples to use during each iteration, as set by the user.

Protected Member Functions

virtual void computeTransformation (PointCloudSource &output)
 Rigid transformation computation method.

Protected Attributes

FeatureCloudConstPtr input_features_
 The source point cloud's feature descriptors.
FeatureCloudConstPtr target_features_
 The target point cloud's feature descriptors.
int nr_samples_
 The number of samples to use during each iteration.
float min_sample_distance_
 The minimum distances between samples.
FeatureKdTreePtr feature_tree_
 The KdTree used to compare feature descriptors.

Detailed Description

template<typename PointSource, typename PointTarget, typename FeatureT>
class pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >

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

Definition at line 51 of file ia_ransac.h.


Constructor & Destructor Documentation

template<typename PointSource , typename PointTarget , typename FeatureT >
pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::SampleConsensusInitialAlignment (  )  [inline]

Constructor.

Definition at line 82 of file ia_ransac.h.


Member Function Documentation

template<typename PointSource , typename PointTarget , typename FeatureT >
void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::computeTransformation ( PointCloudSource output  )  [protected, virtual]

Rigid transformation computation method.

Parameters:
output the transformed input point cloud dataset using the rigid transformation found

Implements pcl::Registration< PointSource, PointTarget >.

Definition at line 182 of file ia_ransac.hpp.

template<typename PointSource , typename PointTarget , typename FeatureT >
float pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::getMinSampleDistance (  )  [inline]

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

Definition at line 116 of file ia_ransac.h.

template<typename PointSource , typename PointTarget , typename FeatureT >
int pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::getNumberOfSamples (  )  [inline]

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

Definition at line 126 of file ia_ransac.h.

template<typename PointSource , typename PointTarget , typename FeatureT >
FeatureCloudConstPtr const pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::getSourceFeatures (  )  [inline]

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

Definition at line 96 of file ia_ransac.h.

template<typename PointSource , typename PointTarget , typename FeatureT >
FeatureCloudConstPtr const pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::getTargetFeatures (  )  [inline]

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

Definition at line 106 of file ia_ransac.h.

template<typename PointSource , typename PointTarget , typename FeatureT >
void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::setMinSampleDistance ( float  min_sample_distance  )  [inline]

Set the minimum distances between samples.

Parameters:
min_sample_distance the minimum distances between samples

Definition at line 112 of file ia_ransac.h.

template<typename PointSource , typename PointTarget , typename FeatureT >
void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::setNumberOfSamples ( int  nr_samples  )  [inline]

Set the number of samples to use during each iteration.

Parameters:
nr_samples the number of samples to use during each iteration

Definition at line 122 of file ia_ransac.h.

template<typename PointSource , typename PointTarget , typename FeatureT >
void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::setSourceFeatures ( const FeatureCloudConstPtr &  features  ) 

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

Parameters:
features the source point cloud's features

Definition at line 40 of file ia_ransac.hpp.

template<typename PointSource , typename PointTarget , typename FeatureT >
void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::setTargetFeatures ( const FeatureCloudConstPtr &  features  ) 

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

Parameters:
features the target point cloud's features

Definition at line 53 of file ia_ransac.hpp.


Member Data Documentation

template<typename PointSource , typename PointTarget , typename FeatureT >
FeatureKdTreePtr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::feature_tree_ [protected]

The KdTree used to compare feature descriptors.

Definition at line 184 of file ia_ransac.h.

template<typename PointSource , typename PointTarget , typename FeatureT >
FeatureCloudConstPtr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::input_features_ [protected]

The source point cloud's feature descriptors.

Definition at line 172 of file ia_ransac.h.

template<typename PointSource , typename PointTarget , typename FeatureT >
float pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::min_sample_distance_ [protected]

The minimum distances between samples.

Definition at line 181 of file ia_ransac.h.

template<typename PointSource , typename PointTarget , typename FeatureT >
int pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::nr_samples_ [protected]

The number of samples to use during each iteration.

Definition at line 178 of file ia_ransac.h.

template<typename PointSource , typename PointTarget , typename FeatureT >
FeatureCloudConstPtr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::target_features_ [protected]

The target point cloud's feature descriptors.

Definition at line 175 of file ia_ransac.h.


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