SampleConsensusModel represents the base model class. All sample consensus models must inherit from this class. More...

#include <sac_model.h>

Inheritance diagram for pcl::SampleConsensusModel< PointT >:

[legend]

List of all members.

Public Types
typedef boost::shared_ptr < const SampleConsensusModel >	ConstPtr
typedef pcl::PointCloud< PointT >	PointCloud
typedef pcl::PointCloud < PointT >::ConstPtr	PointCloudConstPtr
typedef pcl::PointCloud < PointT >::Ptr	PointCloudPtr
typedef boost::shared_ptr < SampleConsensusModel >	Ptr
typedef pcl::search::Search < PointT >::Ptr	SearchPtr
Public Member Functions
virtual bool	computeModelCoefficients (const std::vector< int > &samples, Eigen::VectorXf &model_coefficients)=0
	Check whether the given index samples can form a valid model, compute the model coefficients from these samples and store them in model_coefficients. Pure virtual.
double	computeVariance (const std::vector< double > &error_sqr_dists)
	Compute the variance of the errors to the model.
double	computeVariance ()
	Compute the variance of the errors to the model from the internally estimated vector of distances. The model must be computed first (or at least selectWithinDistance must be called).
virtual int	countWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold)=0
	Count all the points which respect the given model coefficients as inliers. Pure virtual.
virtual bool	doSamplesVerifyModel (const std::set< int > &indices, const Eigen::VectorXf &model_coefficients, const double threshold)=0
	Verify whether a subset of indices verifies a given set of model coefficients. Pure virtual.
virtual void	getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector< double > &distances)=0
	Compute all distances from the cloud data to a given model. Pure virtual.
boost::shared_ptr< std::vector < int > >	getIndices () const
	Get a pointer to the vector of indices used.
PointCloudConstPtr	getInputCloud () const
	Get a pointer to the input point cloud dataset.
virtual SacModel	getModelType () const =0
	Return an unique id for each type of model employed.
void	getRadiusLimits (double &min_radius, double &max_radius)
	Get the minimum and maximum allowable radius limits for the model as set by the user.
virtual void	getSamples (int &iterations, std::vector< int > &samples)
	Get a set of random data samples and return them as point indices.
unsigned int	getSampleSize () const
	Return the size of a sample from which a model is computed.
void	getSamplesMaxDist (double &radius)
	Get maximum distance allowed when drawing random samples.
virtual void	optimizeModelCoefficients (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients)=0
	Recompute the model coefficients using the given inlier set and return them to the user. Pure virtual.
virtual void	projectPoints (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true)=0
	Create a new point cloud with inliers projected onto the model. Pure virtual.
	SampleConsensusModel (const PointCloudConstPtr &cloud, bool random=false)
	Constructor for base SampleConsensusModel.
	SampleConsensusModel (const PointCloudConstPtr &cloud, const std::vector< int > &indices, bool random=false)
	Constructor for base SampleConsensusModel.
virtual void	selectWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold, std::vector< int > &inliers)=0
	Select all the points which respect the given model coefficients as inliers. Pure virtual.
void	setIndices (const boost::shared_ptr< std::vector< int > > &indices)
	Provide a pointer to the vector of indices that represents the input data.
void	setIndices (const std::vector< int > &indices)
	Provide the vector of indices that represents the input data.
virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset.
void	setRadiusLimits (const double &min_radius, const double &max_radius)
	Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate a radius)
void	setSamplesMaxDist (const double &radius, SearchPtr search)
	Set the maximum distance allowed when drawing random samples.
virtual	~SampleConsensusModel ()
	Destructor for base SampleConsensusModel.
Protected Member Functions
void	drawIndexSample (std::vector< int > &sample)
	Fills a sample array with random samples from the indices_ vector.
void	drawIndexSampleRadius (std::vector< int > &sample)
	Fills a sample array with one random sample from the indices_ vector and other random samples that are closer than samples_radius_.
virtual bool	isModelValid (const Eigen::VectorXf &model_coefficients)=0
	Check whether a model is valid given the user constraints.
virtual bool	isSampleGood (const std::vector< int > &samples) const =0
	Check if a sample of indices results in a good sample of points indices. Pure virtual.
int	rnd ()
	Boost-based random number generator.
	SampleConsensusModel (bool random=false)
	Empty constructor for base SampleConsensusModel.
Protected Attributes
std::vector< double >	error_sqr_dists_
	A vector holding the distances to the computed model. Used internally.
boost::shared_ptr< std::vector < int > >	indices_
	A pointer to the vector of point indices to use.
PointCloudConstPtr	input_
	A boost shared pointer to the point cloud data array.
double	radius_max_
double	radius_min_
	The minimum and maximum radius limits for the model. Applicable to all models that estimate a radius.
boost::mt19937	rng_alg_
	Boost-based random number generator algorithm.
boost::shared_ptr < boost::uniform_int<> >	rng_dist_
	Boost-based random number generator distribution.
boost::shared_ptr < boost::variate_generator < boost::mt19937 &, boost::uniform_int<> > >	rng_gen_
	Boost-based random number generator.
double	samples_radius_
	The maximum distance of subsequent samples from the first (radius search)
SearchPtr	samples_radius_search_
	The search object for picking subsequent samples using radius search.
std::vector< int >	shuffled_indices_
Static Protected Attributes
static const unsigned int	max_sample_checks_ = 1000
Friends
class	ProgressiveSampleConsensus< PointT >

Detailed Description

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

SampleConsensusModel represents the base model class. All sample consensus models must inherit from this class.

Author:: Radu B. Rusu

Definition at line 66 of file sac_model.h.

Member Typedef Documentation

template<typename PointT>

typedef boost::shared_ptr<const SampleConsensusModel> pcl::SampleConsensusModel< PointT >::ConstPtr

Reimplemented in pcl::SampleConsensusModelCircle3D< PointT >, and pcl::SampleConsensusModelRegistration2D< PointT >.

Definition at line 75 of file sac_model.h.

template<typename PointT>

typedef pcl::PointCloud<PointT> pcl::SampleConsensusModel< PointT >::PointCloud

Definition at line 69 of file sac_model.h.

template<typename PointT>

typedef pcl::PointCloud<PointT>::ConstPtr pcl::SampleConsensusModel< PointT >::PointCloudConstPtr

Definition at line 70 of file sac_model.h.

template<typename PointT>

typedef pcl::PointCloud<PointT>::Ptr pcl::SampleConsensusModel< PointT >::PointCloudPtr

Definition at line 71 of file sac_model.h.

template<typename PointT>

typedef boost::shared_ptr<SampleConsensusModel> pcl::SampleConsensusModel< PointT >::Ptr

Definition at line 74 of file sac_model.h.

template<typename PointT>

typedef pcl::search::Search<PointT>::Ptr pcl::SampleConsensusModel< PointT >::SearchPtr

Definition at line 72 of file sac_model.h.

Constructor & Destructor Documentation

template<typename PointT>

pcl::SampleConsensusModel< PointT >::SampleConsensusModel ( bool random = false ) [inline, protected]

Empty constructor for base SampleConsensusModel.

Parameters:

[in] random if true set the random seed to the current time, else set to 12345 (default: false)

Definition at line 81 of file sac_model.h.

template<typename PointT>

pcl::SampleConsensusModel< PointT >::SampleConsensusModel	(	const PointCloudConstPtr &	cloud,
		bool	random = `false`
	)		`[inline]`

Constructor for base SampleConsensusModel.

Parameters:

[in]	cloud	the input point cloud dataset
[in]	random	if true set the random seed to the current time, else set to 12345 (default: false)

Definition at line 108 of file sac_model.h.

template<typename PointT>

pcl::SampleConsensusModel< PointT >::SampleConsensusModel	(	const PointCloudConstPtr &	cloud,
		const std::vector< int > &	indices,
		bool	random = `false`
	)		`[inline]`

Constructor for base SampleConsensusModel.

Parameters:

[in]	cloud	the input point cloud dataset
[in]	indices	a vector of point indices to be used from cloud
[in]	random	if true set the random seed to the current time, else set to 12345 (default: false)

Definition at line 138 of file sac_model.h.

template<typename PointT>

virtual pcl::SampleConsensusModel< PointT >::~SampleConsensusModel ( ) [inline, virtual]

Destructor for base SampleConsensusModel.

Definition at line 170 of file sac_model.h.

Member Function Documentation

template<typename PointT>

virtual bool pcl::SampleConsensusModel< PointT >::computeModelCoefficients	(	const std::vector< int > &	samples,
		Eigen::VectorXf &	model_coefficients
	)		`[pure virtual]`

Check whether the given index samples can form a valid model, compute the model coefficients from these samples and store them in model_coefficients. Pure virtual.

Parameters:

[in]	samples	the point indices found as possible good candidates for creating a valid model
[out]	model_coefficients	the computed model coefficients

Implemented in pcl::SampleConsensusModelCone< PointT, PointNT >, pcl::SampleConsensusModelPlane< PointT >, pcl::SampleConsensusModelCylinder< PointT, PointNT >, pcl::SampleConsensusModelRegistration< PointT >, pcl::SampleConsensusModelSphere< PointT >, pcl::SampleConsensusModelCircle2D< PointT >, pcl::SampleConsensusModelCircle3D< PointT >, pcl::SampleConsensusModelStick< PointT >, and pcl::SampleConsensusModelLine< PointT >.

template<typename PointT>

double pcl::SampleConsensusModel< PointT >::computeVariance ( const std::vector< double > & error_sqr_dists ) [inline]

Compute the variance of the errors to the model.

Parameters:

[in] error_sqr_dists a vector holding the distances

Definition at line 413 of file sac_model.h.

template<typename PointT>

double pcl::SampleConsensusModel< PointT >::computeVariance ( ) [inline]

Compute the variance of the errors to the model from the internally estimated vector of distances. The model must be computed first (or at least selectWithinDistance must be called).

Definition at line 426 of file sac_model.h.

template<typename PointT>

virtual int pcl::SampleConsensusModel< PointT >::countWithinDistance	(	const Eigen::VectorXf &	model_coefficients,
		const double	threshold
	)		`[pure virtual]`

Count all the points which respect the given model coefficients as inliers. Pure virtual.

Parameters:

[in]	model_coefficients	the coefficients of a model that we need to compute distances to
[in]	threshold	a maximum admissible distance threshold for determining the inliers from the outliers

Returns:: the resultant number of inliers

template<typename PointT>

virtual bool pcl::SampleConsensusModel< PointT >::doSamplesVerifyModel	(	const std::set< int > &	indices,
		const Eigen::VectorXf &	model_coefficients,
		const double	threshold
	)		`[pure virtual]`

Verify whether a subset of indices verifies a given set of model coefficients. Pure virtual.

Parameters:

[in]	indices	the data indices that need to be tested against the model
[in]	model_coefficients	the set of model coefficients
[in]	threshold	a maximum admissible distance threshold for determining the inliers from the outliers

Implemented in pcl::SampleConsensusModelCone< PointT, PointNT >, pcl::SampleConsensusModelPlane< PointT >, pcl::SampleConsensusModelCylinder< PointT, PointNT >, pcl::SampleConsensusModelRegistration< PointT >, pcl::SampleConsensusModelSphere< PointT >, pcl::SampleConsensusModelCircle2D< PointT >, pcl::SampleConsensusModelCircle3D< PointT >, pcl::SampleConsensusModelStick< PointT >, and pcl::SampleConsensusModelLine< PointT >.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::drawIndexSample ( std::vector< int > & sample ) [inline, protected]

Fills a sample array with random samples from the indices_ vector.

Parameters:

[out] sample the set of indices of target_ to analyze

Definition at line 441 of file sac_model.h.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::drawIndexSampleRadius ( std::vector< int > & sample ) [inline, protected]

Fills a sample array with one random sample from the indices_ vector and other random samples that are closer than samples_radius_.

Parameters:

[out] sample the set of indices of target_ to analyze

Definition at line 458 of file sac_model.h.

template<typename PointT>

virtual void pcl::SampleConsensusModel< PointT >::getDistancesToModel	(	const Eigen::VectorXf &	model_coefficients,
		std::vector< double > &	distances
	)		`[pure virtual]`

Compute all distances from the cloud data to a given model. Pure virtual.

Parameters:

[in]	model_coefficients	the coefficients of a model that we need to compute distances to
[out]	distances	the resultant estimated distances

template<typename PointT>

boost::shared_ptr<std::vector<int> > pcl::SampleConsensusModel< PointT >::getIndices ( ) const [inline]

Get a pointer to the vector of indices used.

Definition at line 345 of file sac_model.h.

template<typename PointT>

PointCloudConstPtr pcl::SampleConsensusModel< PointT >::getInputCloud ( ) const [inline]

Get a pointer to the input point cloud dataset.

Definition at line 321 of file sac_model.h.

template<typename PointT>

virtual SacModel pcl::SampleConsensusModel< PointT >::getModelType ( ) const [pure virtual]

Return an unique id for each type of model employed.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::getRadiusLimits	(	double &	min_radius,
		double &	max_radius
	)		`[inline]`

Get the minimum and maximum allowable radius limits for the model as set by the user.

Parameters:

[out]	min_radius	the resultant minimum radius model
[out]	max_radius	the resultant maximum radius model

Definition at line 381 of file sac_model.h.

template<typename PointT>

virtual void pcl::SampleConsensusModel< PointT >::getSamples	(	int &	iterations,
		std::vector< int > &	samples
	)		`[inline, virtual]`

Get a set of random data samples and return them as point indices.

Parameters:

[out]	iterations	the internal number of iterations used by SAC methods
[out]	samples	the resultant model samples

Definition at line 178 of file sac_model.h.

template<typename PointT>

unsigned int pcl::SampleConsensusModel< PointT >::getSampleSize ( ) const [inline]

Return the size of a sample from which a model is computed.

Definition at line 353 of file sac_model.h.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::getSamplesMaxDist ( double & radius ) [inline]

Get maximum distance allowed when drawing random samples.

Parameters:

[out] radius the maximum distance (L2 norm)

Definition at line 402 of file sac_model.h.

template<typename PointT>

virtual bool pcl::SampleConsensusModel< PointT >::isModelValid ( const Eigen::VectorXf & model_coefficients ) [inline, protected, pure virtual]

Check whether a model is valid given the user constraints.

Parameters:

[in] model_coefficients the set of model coefficients

template<typename PointT>

virtual bool pcl::SampleConsensusModel< PointT >::isSampleGood ( const std::vector< int > & samples ) const [protected, pure virtual]

Check if a sample of indices results in a good sample of points indices. Pure virtual.

Parameters:

[in] samples the resultant index samples

Implemented in pcl::SampleConsensusModelCone< PointT, PointNT >, pcl::SampleConsensusModelCylinder< PointT, PointNT >, pcl::SampleConsensusModelPlane< PointT >, pcl::SampleConsensusModelRegistration< PointT >, pcl::SampleConsensusModelSphere< PointT >, pcl::SampleConsensusModelCircle2D< PointT >, pcl::SampleConsensusModelCircle3D< PointT >, pcl::SampleConsensusModelStick< PointT >, pcl::SampleConsensusModelLine< PointT >, and pcl::SampleConsensusModelRegistration2D< PointT >.

template<typename PointT>

virtual void pcl::SampleConsensusModel< PointT >::optimizeModelCoefficients	(	const std::vector< int > &	inliers,
		const Eigen::VectorXf &	model_coefficients,
		Eigen::VectorXf &	optimized_coefficients
	)		`[pure virtual]`

Recompute the model coefficients using the given inlier set and return them to the user. Pure virtual.

Note:: : these are the coefficients of the model after refinement (e.g., after a least-squares optimization)

Parameters:

[in]	inliers	the data inliers supporting the model
[in]	model_coefficients	the initial guess for the model coefficients
[out]	optimized_coefficients	the resultant recomputed coefficients after non-linear optimization

Implemented in pcl::SampleConsensusModelCone< PointT, PointNT >, pcl::SampleConsensusModelPlane< PointT >, pcl::SampleConsensusModelCylinder< PointT, PointNT >, pcl::SampleConsensusModelRegistration< PointT >, pcl::SampleConsensusModelSphere< PointT >, pcl::SampleConsensusModelCircle2D< PointT >, pcl::SampleConsensusModelCircle3D< PointT >, pcl::SampleConsensusModelStick< PointT >, and pcl::SampleConsensusModelLine< PointT >.

template<typename PointT>

virtual void pcl::SampleConsensusModel< PointT >::projectPoints	(	const std::vector< int > &	inliers,
		const Eigen::VectorXf &	model_coefficients,
		PointCloud &	projected_points,
		bool	copy_data_fields = `true`
	)		`[pure virtual]`

Create a new point cloud with inliers projected onto the model. Pure virtual.

Parameters:

[in]	inliers	the data inliers that we want to project on the model
[in]	model_coefficients	the coefficients of a model
[out]	projected_points	the resultant projected points
[in]	copy_data_fields	set to true (default) if we want the projected_points cloud to be an exact copy of the input dataset minus the point projections on the plane model

Implemented in pcl::SampleConsensusModelCone< PointT, PointNT >, pcl::SampleConsensusModelPlane< PointT >, pcl::SampleConsensusModelCylinder< PointT, PointNT >, pcl::SampleConsensusModelRegistration< PointT >, pcl::SampleConsensusModelSphere< PointT >, pcl::SampleConsensusModelCircle2D< PointT >, pcl::SampleConsensusModelCircle3D< PointT >, pcl::SampleConsensusModelStick< PointT >, and pcl::SampleConsensusModelLine< PointT >.

template<typename PointT>

int pcl::SampleConsensusModel< PointT >::rnd ( ) [inline, protected]

Boost-based random number generator.

Definition at line 544 of file sac_model.h.

template<typename PointT>

virtual void pcl::SampleConsensusModel< PointT >::selectWithinDistance	(	const Eigen::VectorXf &	model_coefficients,
		const double	threshold,
		std::vector< int > &	inliers
	)		`[pure virtual]`

Select all the points which respect the given model coefficients as inliers. Pure virtual.

Parameters:

[in]	model_coefficients	the coefficients of a model that we need to compute distances to
[in]	threshold	a maximum admissible distance threshold for determining the inliers from the outliers
[out]	inliers	the resultant model inliers

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::setIndices ( const boost::shared_ptr< std::vector< int > > & indices ) [inline]

Provide a pointer to the vector of indices that represents the input data.

Parameters:

[in] indices a pointer to the vector of indices that represents the input data.

Definition at line 327 of file sac_model.h.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::setIndices ( const std::vector< int > & indices ) [inline]

Provide the vector of indices that represents the input data.

Parameters:

[out] indices the vector of indices that represents the input data.

Definition at line 337 of file sac_model.h.

template<typename PointT>

virtual void pcl::SampleConsensusModel< PointT >::setInputCloud ( const PointCloudConstPtr & cloud ) [inline, virtual]

Provide a pointer to the input dataset.

Parameters:

[in] cloud the const boost shared pointer to a PointCloud message

Reimplemented in pcl::SampleConsensusModelRegistration< PointT >.

Definition at line 304 of file sac_model.h.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::setRadiusLimits	(	const double &	min_radius,
		const double &	max_radius
	)		`[inline]`

Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate a radius)

Parameters:

[in]	min_radius	the minimum radius model
[in]	max_radius	the maximum radius model

Todo:: change this to set limits on the entire model

Definition at line 368 of file sac_model.h.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::setSamplesMaxDist	(	const double &	radius,
		SearchPtr	search
	)		`[inline]`

Set the maximum distance allowed when drawing random samples.

Parameters:

[in] radius the maximum distance (L2 norm)

Definition at line 391 of file sac_model.h.

Friends And Related Function Documentation

template<typename PointT>

friend class ProgressiveSampleConsensus< PointT > [friend]

Definition at line 407 of file sac_model.h.

Member Data Documentation

template<typename PointT>

std::vector<double> pcl::SampleConsensusModel< PointT >::error_sqr_dists_ [protected]

A vector holding the distances to the computed model. Used internally.

Definition at line 540 of file sac_model.h.

template<typename PointT>

boost::shared_ptr<std::vector<int> > pcl::SampleConsensusModel< PointT >::indices_ [protected]

A pointer to the vector of point indices to use.

Definition at line 511 of file sac_model.h.

template<typename PointT>

PointCloudConstPtr pcl::SampleConsensusModel< PointT >::input_ [protected]

A boost shared pointer to the point cloud data array.

Definition at line 508 of file sac_model.h.

template<typename PointT>

const unsigned int pcl::SampleConsensusModel< PointT >::max_sample_checks_ = 1000 [static, protected]

The maximum number of samples to try until we get a good one

Definition at line 514 of file sac_model.h.

template<typename PointT>

double pcl::SampleConsensusModel< PointT >::radius_max_ [protected]

Definition at line 519 of file sac_model.h.

template<typename PointT>

double pcl::SampleConsensusModel< PointT >::radius_min_ [protected]

The minimum and maximum radius limits for the model. Applicable to all models that estimate a radius.

Definition at line 519 of file sac_model.h.

template<typename PointT>

boost::mt19937 pcl::SampleConsensusModel< PointT >::rng_alg_ [protected]

Boost-based random number generator algorithm.

Definition at line 531 of file sac_model.h.

template<typename PointT>

boost::shared_ptr<boost::uniform_int<> > pcl::SampleConsensusModel< PointT >::rng_dist_ [protected]

Boost-based random number generator distribution.

Definition at line 534 of file sac_model.h.

template<typename PointT>

boost::shared_ptr<boost::variate_generator< boost::mt19937&, boost::uniform_int<> > > pcl::SampleConsensusModel< PointT >::rng_gen_ [protected]

Boost-based random number generator.

Definition at line 537 of file sac_model.h.

template<typename PointT>

double pcl::SampleConsensusModel< PointT >::samples_radius_ [protected]

The maximum distance of subsequent samples from the first (radius search)

Definition at line 522 of file sac_model.h.

template<typename PointT>

SearchPtr pcl::SampleConsensusModel< PointT >::samples_radius_search_ [protected]

The search object for picking subsequent samples using radius search.

Definition at line 525 of file sac_model.h.

template<typename PointT>

std::vector<int> pcl::SampleConsensusModel< PointT >::shuffled_indices_ [protected]

Data containing a shuffled version of the indices. This is used and modified when drawing samples.

Definition at line 528 of file sac_model.h.

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

sac_model.h

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Static Protected Attributes

Friends

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Friends And Related Function Documentation

Member Data Documentation

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