MEstimatorSampleConsensus represents an implementation of the MSAC (M-estimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S. More...

#include <pcl/sample_consensus/msac.h>

Inheritance diagram for pcl::MEstimatorSampleConsensus< PointT >:

[legend]

Collaboration diagram for pcl::MEstimatorSampleConsensus< PointT >:

[legend]

List of all members.

Public Types
typedef boost::shared_ptr < SampleConsensus >	Ptr
typedef boost::shared_ptr < const SampleConsensus >	ConstPtr
Public Member Functions
	MEstimatorSampleConsensus (const SampleConsensusModelPtr &model)
	MSAC (M-estimator SAmple Consensus) main constructor.
	MEstimatorSampleConsensus (const SampleConsensusModelPtr &model, double threshold)
	MSAC (M-estimator SAmple Consensus) main constructor.
bool	computeModel (int debug_verbosity_level=0)
	Compute the actual model and find the inliers.
void	setDistanceThreshold (double threshold)
	Set the distance to model threshold.
double	getDistanceThreshold ()
	Get the distance to model threshold, as set by the user.
void	setMaxIterations (int max_iterations)
	Set the maximum number of iterations.
int	getMaxIterations ()
	Get the maximum number of iterations, as set by the user.
void	setProbability (double probability)
	Set the desired probability of choosing at least one sample free from outliers.
double	getProbability ()
	Obtain the probability of choosing at least one sample free from outliers, as set by the user.
void	getRandomSamples (const boost::shared_ptr< std::vector< int > > &indices, size_t nr_samples, std::set< int > &indices_subset)
	Get a set of randomly selected indices.
void	getModel (std::vector< int > &model)
	Return the best model found so far.
void	getInliers (std::vector< int > &inliers)
	Return the best set of inliers found so far for this model.
void	getModelCoefficients (Eigen::VectorXf &model_coefficients)
	Return the model coefficients of the best model found so far.

Detailed Description

template<typename PointT>
class pcl::MEstimatorSampleConsensus< PointT >

MEstimatorSampleConsensus represents an implementation of the MSAC (M-estimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S.

Torr and A. Zisserman, Computer Vision and Image Understanding, vol 78, 2000.

Author:: Radu Bogdan Rusu

Definition at line 55 of file msac.h.

Member Typedef Documentation

typedef boost::shared_ptr<const SampleConsensus> pcl::SampleConsensus< PointT >::ConstPtr [inherited]

Definition at line 63 of file sac.h.

typedef boost::shared_ptr<SampleConsensus> pcl::SampleConsensus< PointT >::Ptr [inherited]

Definition at line 59 of file sac.h.

Constructor & Destructor Documentation

template<typename PointT >

pcl::MEstimatorSampleConsensus< PointT >::MEstimatorSampleConsensus ( const SampleConsensusModelPtr & model ) [inline]

MSAC (M-estimator SAmple Consensus) main constructor.

Parameters:

model a Sample Consensus model

Definition at line 72 of file msac.h.

template<typename PointT >

pcl::MEstimatorSampleConsensus< PointT >::MEstimatorSampleConsensus	(	const SampleConsensusModelPtr &	model,
		double	threshold
	)		`[inline]`

MSAC (M-estimator SAmple Consensus) main constructor.

Parameters:

model	a Sample Consensus model
threshold	distance to model threshold

Definition at line 82 of file msac.h.

Member Function Documentation

template<typename PointT >

bool pcl::MEstimatorSampleConsensus< PointT >::computeModel ( int debug_verbosity_level = 0 ) [virtual]

Compute the actual model and find the inliers.

Parameters:

debug_verbosity_level enable/disable on-screen debug information and set the verbosity level

Implements pcl::SampleConsensus< PointT >.

Definition at line 45 of file msac.hpp.

double pcl::SampleConsensus< PointT >::getDistanceThreshold ( ) [inline, inherited]

Get the distance to model threshold, as set by the user.

Definition at line 91 of file sac.h.

void pcl::SampleConsensus< PointT >::getInliers ( std::vector< int > & inliers ) [inline, inherited]

Return the best set of inliers found so far for this model.

Parameters:

inliers the resultant set of inliers

Definition at line 136 of file sac.h.

int pcl::SampleConsensus< PointT >::getMaxIterations ( ) [inline, inherited]

Get the maximum number of iterations, as set by the user.

Definition at line 99 of file sac.h.

void pcl::SampleConsensus< PointT >::getModel ( std::vector< int > & model ) [inline, inherited]

Return the best model found so far.

Parameters:

model the resultant model

Definition at line 131 of file sac.h.

void pcl::SampleConsensus< PointT >::getModelCoefficients ( Eigen::VectorXf & model_coefficients ) [inline, inherited]

Return the model coefficients of the best model found so far.

Parameters:

model_coefficients the resultant model coefficients

Definition at line 141 of file sac.h.

double pcl::SampleConsensus< PointT >::getProbability ( ) [inline, inherited]

Obtain the probability of choosing at least one sample free from outliers, as set by the user.

Definition at line 108 of file sac.h.

void pcl::SampleConsensus< PointT >::getRandomSamples	(	const boost::shared_ptr< std::vector< int > > &	indices,
		size_t	nr_samples,
		std::set< int > &	indices_subset
	)		`[inline, inherited]`

Get a set of randomly selected indices.

Parameters:

indices	the input indices vector
nr_samples	the desired number of point indices to randomly select
indices_subset	the resultant output set of randomly selected indices

Reimplemented in pcl::ProgressiveSampleConsensus< PointT >.

Definition at line 119 of file sac.h.

void pcl::SampleConsensus< PointT >::setDistanceThreshold ( double threshold ) [inline, inherited]

Set the distance to model threshold.

Parameters:

threshold distance to model threshold

Definition at line 88 of file sac.h.

void pcl::SampleConsensus< PointT >::setMaxIterations ( int max_iterations ) [inline, inherited]

Set the maximum number of iterations.

Parameters:

max_iterations maximum number of iterations

Definition at line 96 of file sac.h.

void pcl::SampleConsensus< PointT >::setProbability ( double probability ) [inline, inherited]

Set the desired probability of choosing at least one sample free from outliers.

Parameters:

probability the desired probability of choosing at least one sample free from outliers

Note:: internally, the probability is set to 99% (0.99) by default.

Definition at line 105 of file sac.h.

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

/builddir/build/BUILD/PCL-1.3.1-Source/sample_consensus/include/pcl/sample_consensus/msac.h
/builddir/build/BUILD/PCL-1.3.1-Source/sample_consensus/include/pcl/sample_consensus/impl/msac.hpp

Public Types

Public Member Functions

Detailed Description

template<typename PointT> class pcl::MEstimatorSampleConsensus< PointT >

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

template<typename PointT>
class pcl::MEstimatorSampleConsensus< PointT >