SampleConsensusModel represents the base model class. More...

#include <pcl/sample_consensus/sac_model.h>

Inheritance diagram for pcl::SampleConsensusModel< PointT >:

Collaboration diagram for pcl::SampleConsensusModel< PointT >:

Public Types
using	PointCloud = pcl::PointCloud< PointT >

using	PointCloudConstPtr = typename PointCloud::ConstPtr

using	PointCloudPtr = typename PointCloud::Ptr

using	SearchPtr = typename pcl::search::Search< PointT >::Ptr

using	Ptr = shared_ptr< SampleConsensusModel< PointT > >

using	ConstPtr = shared_ptr< const SampleConsensusModel< PointT > >

Public Member Functions
	SampleConsensusModel (const PointCloudConstPtr &cloud, bool random=false)
	Constructor for base SampleConsensusModel. More...

	SampleConsensusModel (const PointCloudConstPtr &cloud, const Indices &indices, bool random=false)
	Constructor for base SampleConsensusModel. More...

virtual	~SampleConsensusModel ()=default
	Destructor for base SampleConsensusModel. More...

virtual void	getSamples (int &iterations, Indices &samples)
	Get a set of random data samples and return them as point indices. More...

virtual bool	computeModelCoefficients (const Indices &samples, Eigen::VectorXf &model_coefficients) const =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. More...

virtual void	optimizeModelCoefficients (const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const =0
	Recompute the model coefficients using the given inlier set and return them to the user. More...

virtual void	getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) const =0
	Compute all distances from the cloud data to a given model. More...

virtual void	selectWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)=0
	Select all the points which respect the given model coefficients as inliers. More...

virtual std::size_t	countWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold) const =0
	Count all the points which respect the given model coefficients as inliers. More...

virtual void	projectPoints (const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true) const =0
	Create a new point cloud with inliers projected onto the model. More...

virtual bool	doSamplesVerifyModel (const std::set< index_t > &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const =0
	Verify whether a subset of indices verifies a given set of model coefficients. More...

virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset. More...

PointCloudConstPtr	getInputCloud () const
	Get a pointer to the input point cloud dataset. More...

void	setIndices (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...

void	setIndices (const Indices &indices)
	Provide the vector of indices that represents the input data. More...

IndicesPtr	getIndices () const
	Get a pointer to the vector of indices used. More...

virtual SacModel	getModelType () const =0
	Return a unique id for each type of model employed. More...

const std::string &	getClassName () const
	Get a string representation of the name of this class. More...

unsigned int	getSampleSize () const
	Return the size of a sample from which the model is computed. More...

unsigned int	getModelSize () const
	Return the number of coefficients in the model. More...

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) More...

void	getRadiusLimits (double &min_radius, double &max_radius) const
	Get the minimum and maximum allowable radius limits for the model as set by the user. More...

void	setModelConstraints (std::function< bool(const Eigen::VectorXf &)> function)
	This can be used to impose any kind of constraint on the model, e.g. More...

void	setSamplesMaxDist (const double &radius, SearchPtr search)
	Set the maximum distance allowed when drawing random samples. More...

void	getSamplesMaxDist (double &radius) const
	Get maximum distance allowed when drawing random samples. More...

double	computeVariance (const std::vector< double > &error_sqr_dists) const
	Compute the variance of the errors to the model. More...

double	computeVariance () const
	Compute the variance of the errors to the model from the internally estimated vector of distances. More...

Protected Member Functions
	SampleConsensusModel (bool random=false)
	Empty constructor for base SampleConsensusModel. More...

void	drawIndexSample (Indices &sample)
	Fills a sample array with random samples from the indices_ vector. More...

void	drawIndexSampleRadius (Indices &sample)
	Fills a sample array with one random sample from the indices_ vector and other random samples that are closer than samples_radius_. More...

virtual bool	isModelValid (const Eigen::VectorXf &model_coefficients) const
	Check whether a model is valid given the user constraints. More...

virtual bool	isSampleGood (const Indices &samples) const =0
	Check if a sample of indices results in a good sample of points indices. More...

int	rnd ()
	Boost-based random number generator. More...

Protected Attributes
std::string	model_name_
	The model name. More...

PointCloudConstPtr	input_
	A boost shared pointer to the point cloud data array. More...

IndicesPtr	indices_
	A pointer to the vector of point indices to use. More...

double	radius_min_
	The minimum and maximum radius limits for the model. More...

double	radius_max_

double	samples_radius_
	The maximum distance of subsequent samples from the first (radius search) More...

SearchPtr	samples_radius_search_
	The search object for picking subsequent samples using radius search. More...

Indices	shuffled_indices_
	Data containing a shuffled version of the indices. More...

boost::mt19937	rng_alg_
	Boost-based random number generator algorithm. More...

std::shared_ptr< boost::uniform_int<> >	rng_dist_
	Boost-based random number generator distribution. More...

std::shared_ptr< boost::variate_generator< boost::mt19937 &, boost::uniform_int<> > >	rng_gen_
	Boost-based random number generator. More...

std::vector< double >	error_sqr_dists_
	A vector holding the distances to the computed model. More...

unsigned int	sample_size_
	The size of a sample from which the model is computed. More...

unsigned int	model_size_
	The number of coefficients in the model. More...

std::function< bool(const Eigen::VectorXf &)>	custom_model_constraints_
	A user defined function that takes model coefficients and returns whether the model is acceptable or not. More...

Static Protected Attributes
static const unsigned int	max_sample_checks_ = 1000
	The maximum number of samples to try until we get a good one. More...

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 70 of file sac_model.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointT >

using pcl::SampleConsensusModel< PointT >::ConstPtr = shared_ptr<const SampleConsensusModel<PointT> >

Definition at line 79 of file sac_model.h.

◆ PointCloud

template<typename PointT >

using pcl::SampleConsensusModel< PointT >::PointCloud = pcl::PointCloud<PointT>

Definition at line 73 of file sac_model.h.

◆ PointCloudConstPtr

template<typename PointT >

using pcl::SampleConsensusModel< PointT >::PointCloudConstPtr = typename PointCloud::ConstPtr

Definition at line 74 of file sac_model.h.

◆ PointCloudPtr

template<typename PointT >

using pcl::SampleConsensusModel< PointT >::PointCloudPtr = typename PointCloud::Ptr

Definition at line 75 of file sac_model.h.

◆ Ptr

template<typename PointT >

using pcl::SampleConsensusModel< PointT >::Ptr = shared_ptr<SampleConsensusModel<PointT> >

Definition at line 78 of file sac_model.h.

◆ SearchPtr

template<typename PointT >

using pcl::SampleConsensusModel< PointT >::SearchPtr = typename pcl::search::Search<PointT>::Ptr

Definition at line 76 of file sac_model.h.

Constructor & Destructor Documentation

◆ SampleConsensusModel() [1/3]

template<typename PointT >

pcl::SampleConsensusModel< PointT >::SampleConsensusModel ( bool random = false )

inlineprotected

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 85 of file sac_model.h.

◆ SampleConsensusModel() [2/3]

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.

◆ SampleConsensusModel() [3/3]

template<typename PointT >

pcl::SampleConsensusModel< PointT >::SampleConsensusModel	(	const PointCloudConstPtr &	cloud,
		const Indices &	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 134 of file sac_model.h.

◆ ~SampleConsensusModel()

template<typename PointT >

virtual pcl::SampleConsensusModel< PointT >::~SampleConsensusModel ( )

virtualdefault

Destructor for base SampleConsensusModel.

Member Function Documentation

◆ computeModelCoefficients()

template<typename PointT >

virtual bool pcl::SampleConsensusModel< PointT >::computeModelCoefficients	(	const Indices &	samples,
		Eigen::VectorXf &	model_coefficients
	)		const

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. Implementations of this function must be thread-safe.

Parameters

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

◆ computeVariance() [1/2]

template<typename PointT >

double pcl::SampleConsensusModel< PointT >::computeVariance ( ) const

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 451 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::error_sqr_dists_.

◆ computeVariance() [2/2]

template<typename PointT >

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

inline

Compute the variance of the errors to the model.

Parameters

[in] error_sqr_dists a vector holding the distances

Definition at line 437 of file sac_model.h.

◆ countWithinDistance()

template<typename PointT >

virtual std::size_t pcl::SampleConsensusModel< PointT >::countWithinDistance	(	const Eigen::VectorXf &	model_coefficients,
		const double	threshold
	)		const

pure virtual

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

Pure virtual. Implementations of this function must be thread-safe.

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

◆ doSamplesVerifyModel()

template<typename PointT >

virtual bool pcl::SampleConsensusModel< PointT >::doSamplesVerifyModel	(	const std::set< index_t > &	indices,
		const Eigen::VectorXf &	model_coefficients,
		const double	threshold
	)		const

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

◆ drawIndexSample()

template<typename PointT >

void pcl::SampleConsensusModel< PointT >::drawIndexSample ( Indices & sample )

inlineprotected

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 467 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::rnd(), and pcl::SampleConsensusModel< PointT >::shuffled_indices_.

Referenced by pcl::SampleConsensusModel< PointT >::getSamples().

◆ drawIndexSampleRadius()

template<typename PointT >

void pcl::SampleConsensusModel< PointT >::drawIndexSampleRadius ( Indices & sample )

inlineprotected

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 484 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::input_, pcl::SampleConsensusModel< PointT >::rnd(), pcl::SampleConsensusModel< PointT >::samples_radius_, pcl::SampleConsensusModel< PointT >::samples_radius_search_, and pcl::SampleConsensusModel< PointT >::shuffled_indices_.

Referenced by pcl::SampleConsensusModel< PointT >::getSamples().

◆ getClassName()

template<typename PointT >

const std::string& pcl::SampleConsensusModel< PointT >::getClassName ( ) const

inline

Get a string representation of the name of this class.

Definition at line 350 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::model_name_.

Referenced by pcl::SampleConsensusModel< PointT >::isModelValid().

◆ getDistancesToModel()

template<typename PointT >

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

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

◆ getIndices()

template<typename PointT >

IndicesPtr pcl::SampleConsensusModel< PointT >::getIndices ( ) const

inline

Get a pointer to the vector of indices used.

Definition at line 342 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::indices_.

◆ getInputCloud()

template<typename PointT >

PointCloudConstPtr pcl::SampleConsensusModel< PointT >::getInputCloud ( ) const

inline

Get a pointer to the input point cloud dataset.

Definition at line 318 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::input_.

◆ getModelSize()

template<typename PointT >

unsigned int pcl::SampleConsensusModel< PointT >::getModelSize ( ) const

inline

Return the number of coefficients in the model.

Definition at line 364 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::model_size_.

◆ getModelType()

template<typename PointT >

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

pure virtual

Return a unique id for each type of model employed.

◆ getRadiusLimits()

template<typename PointT >

void pcl::SampleConsensusModel< PointT >::getRadiusLimits	(	double &	min_radius,
		double &	max_radius
	)		const

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 389 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::radius_max_, and pcl::SampleConsensusModel< PointT >::radius_min_.

Referenced by pcl::SACSegmentation< PointT >::initSACModel(), and pcl::SACSegmentationFromNormals< PointT, PointNT >::initSACModel().

◆ getSamples()

template<typename PointT >

virtual void pcl::SampleConsensusModel< PointT >::getSamples	(	int &	iterations,
		Indices &	samples
	)

inlinevirtual

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 174 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::drawIndexSample(), pcl::SampleConsensusModel< PointT >::drawIndexSampleRadius(), pcl::SampleConsensusModel< PointT >::getSampleSize(), pcl::SampleConsensusModel< PointT >::indices_, pcl::SampleConsensusModel< PointT >::isSampleGood(), pcl::SampleConsensusModel< PointT >::max_sample_checks_, and pcl::SampleConsensusModel< PointT >::samples_radius_.

◆ getSampleSize()

template<typename PointT >

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

inline

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

Definition at line 357 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::sample_size_.

Referenced by pcl::SampleConsensusModel< PointT >::getSamples().

◆ getSamplesMaxDist()

template<typename PointT >

void pcl::SampleConsensusModel< PointT >::getSamplesMaxDist ( double & radius ) const

inline

Get maximum distance allowed when drawing random samples.

Parameters

[out] radius the maximum distance (L2 norm)

Definition at line 426 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::samples_radius_.

◆ isModelValid()

template<typename PointT >

virtual bool pcl::SampleConsensusModel< PointT >::isModelValid ( const Eigen::VectorXf & model_coefficients ) const

inlineprotectedvirtual

Check whether a model is valid given the user constraints.

Default implementation verifies that the number of coefficients in the supplied model is as expected for this SAC model type. Specific SAC models should extend this function by checking the user constraints (if any).

Parameters

[in] model_coefficients the set of model coefficients

Definition at line 528 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::custom_model_constraints_, pcl::SampleConsensusModel< PointT >::getClassName(), and pcl::SampleConsensusModel< PointT >::model_size_.

◆ isSampleGood()

template<typename PointT >

virtual bool pcl::SampleConsensusModel< PointT >::isSampleGood ( const Indices & samples ) const

protectedpure virtual

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

Pure virtual.

Parameters

[in] samples the resultant index samples

Referenced by pcl::SampleConsensusModel< PointT >::getSamples().

◆ optimizeModelCoefficients()

template<typename PointT >

virtual void pcl::SampleConsensusModel< PointT >::optimizeModelCoefficients	(	const Indices &	inliers,
		const Eigen::VectorXf &	model_coefficients,
		Eigen::VectorXf &	optimized_coefficients
	)		const

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

◆ projectPoints()

template<typename PointT >

virtual void pcl::SampleConsensusModel< PointT >::projectPoints	(	const Indices &	inliers,
		const Eigen::VectorXf &	model_coefficients,
		PointCloud &	projected_points,
		bool	copy_data_fields = `true`
	)		const

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::SampleConsensusModelStick< PointT >, pcl::SampleConsensusModelSphere< PointT >, pcl::SampleConsensusModelPlane< PointT >, pcl::SampleConsensusModelLine< PointT >, pcl::SampleConsensusModelEllipse3D< PointT >, pcl::SampleConsensusModelCylinder< PointT, PointNT >, pcl::SampleConsensusModelCone< PointT, PointNT >, pcl::SampleConsensusModelCircle3D< PointT >, pcl::SampleConsensusModelCircle2D< PointT >, and pcl::SampleConsensusModelRegistration< PointT >.

◆ rnd()

template<typename PointT >

int pcl::SampleConsensusModel< PointT >::rnd ( )

inlineprotected

Boost-based random number generator.

Definition at line 596 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::rng_gen_.

Referenced by pcl::SampleConsensusModel< PointT >::drawIndexSample(), and pcl::SampleConsensusModel< PointT >::drawIndexSampleRadius().

◆ selectWithinDistance()

template<typename PointT >

virtual void pcl::SampleConsensusModel< PointT >::selectWithinDistance	(	const Eigen::VectorXf &	model_coefficients,
		const double	threshold,
		Indices &	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

◆ setIndices() [1/2]

template<typename PointT >

void pcl::SampleConsensusModel< PointT >::setIndices ( const Indices & 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 334 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::indices_, and pcl::SampleConsensusModel< PointT >::shuffled_indices_.

◆ setIndices() [2/2]

template<typename PointT >

void pcl::SampleConsensusModel< PointT >::setIndices ( const IndicesPtr & 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 324 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::indices_, and pcl::SampleConsensusModel< PointT >::shuffled_indices_.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::selectBase().

◆ setInputCloud()

template<typename PointT >

virtual void pcl::SampleConsensusModel< PointT >::setInputCloud ( const PointCloudConstPtr & cloud )

inlinevirtual

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 301 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::indices_, pcl::SampleConsensusModel< PointT >::input_, and pcl::SampleConsensusModel< PointT >::shuffled_indices_.

Referenced by pcl::SampleConsensusModelRegistration< PointT >::setInputCloud().

◆ setModelConstraints()

template<typename PointT >

void pcl::SampleConsensusModel< PointT >::setModelConstraints ( std::function< bool(const Eigen::VectorXf &)> function )

inline

This can be used to impose any kind of constraint on the model, e.g.

that it has a specific direction, size, or anything else.

Parameters

[in] function A function that gets model coefficients and returns whether the model is acceptable or not.

Definition at line 400 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::custom_model_constraints_.

◆ setRadiusLimits()

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 376 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::radius_max_, and pcl::SampleConsensusModel< PointT >::radius_min_.

Referenced by pcl::SACSegmentation< PointT >::initSACModel(), and pcl::SACSegmentationFromNormals< PointT, PointNT >::initSACModel().

◆ setSamplesMaxDist()

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)
	search

Definition at line 415 of file sac_model.h.

References pcl::SampleConsensusModel< PointT >::samples_radius_, and pcl::SampleConsensusModel< PointT >::samples_radius_search_.

Friends And Related Function Documentation

◆ ProgressiveSampleConsensus< PointT >

template<typename PointT >

friend class ProgressiveSampleConsensus< PointT >

friend

Definition at line 426 of file sac_model.h.

Member Data Documentation

◆ custom_model_constraints_

template<typename PointT >

std::function<bool(const Eigen::VectorXf &)> pcl::SampleConsensusModel< PointT >::custom_model_constraints_

protected

A user defined function that takes model coefficients and returns whether the model is acceptable or not.

Definition at line 602 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< PointT >::isModelValid(), and pcl::SampleConsensusModel< PointT >::setModelConstraints().

◆ error_sqr_dists_

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 586 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< PointT >::computeVariance().

◆ indices_

template<typename PointT >

IndicesPtr pcl::SampleConsensusModel< PointT >::indices_

protected

A pointer to the vector of point indices to use.

Definition at line 557 of file sac_model.h.

Referenced by pcl::SampleConsensusModelRegistration< PointT >::computeOriginalIndexMapping(), pcl::SampleConsensusModel< PointT >::getIndices(), pcl::SampleConsensusModel< PointT >::getSamples(), pcl::SampleConsensusModel< PointT >::setIndices(), and pcl::SampleConsensusModel< PointT >::setInputCloud().

◆ input_

template<typename PointT >

PointCloudConstPtr pcl::SampleConsensusModel< PointT >::input_

protected

A boost shared pointer to the point cloud data array.

Definition at line 554 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< PointT >::drawIndexSampleRadius(), pcl::SampleConsensusModel< PointT >::getInputCloud(), and pcl::SampleConsensusModel< PointT >::setInputCloud().

◆ max_sample_checks_

template<typename PointT >

const unsigned int pcl::SampleConsensusModel< PointT >::max_sample_checks_ = 1000

staticprotected

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

Definition at line 560 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< PointT >::getSamples().

◆ model_name_

template<typename PointT >

std::string pcl::SampleConsensusModel< PointT >::model_name_

protected

The model name.

Definition at line 551 of file sac_model.h.

◆ model_size_

template<typename PointT >

unsigned int pcl::SampleConsensusModel< PointT >::model_size_

protected

The number of coefficients in the model.

Every subclass should initialize this appropriately.

Definition at line 592 of file sac_model.h.

◆ radius_max_

template<typename PointT >

double pcl::SampleConsensusModel< PointT >::radius_max_

protected

Definition at line 565 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< PointT >::getRadiusLimits(), pcl::SampleConsensusModelSphere< PointT >::isModelValid(), and pcl::SampleConsensusModel< PointT >::setRadiusLimits().

◆ radius_min_

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 565 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< PointT >::getRadiusLimits(), pcl::SampleConsensusModelSphere< PointT >::isModelValid(), and pcl::SampleConsensusModel< PointT >::setRadiusLimits().

◆ rng_alg_

template<typename PointT >

boost::mt19937 pcl::SampleConsensusModel< PointT >::rng_alg_

protected

Boost-based random number generator algorithm.

Definition at line 577 of file sac_model.h.

◆ rng_dist_

template<typename PointT >

std::shared_ptr<boost::uniform_int<> > pcl::SampleConsensusModel< PointT >::rng_dist_

protected

Boost-based random number generator distribution.

Definition at line 580 of file sac_model.h.

◆ rng_gen_

template<typename PointT >

std::shared_ptr<boost::variate_generator< boost::mt19937&, boost::uniform_int<> > > pcl::SampleConsensusModel< PointT >::rng_gen_

protected

Boost-based random number generator.

Definition at line 583 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< PointT >::rnd().

◆ sample_size_

template<typename PointT >

unsigned int pcl::SampleConsensusModel< PointT >::sample_size_

protected

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

Every subclass should initialize this appropriately.

Definition at line 589 of file sac_model.h.

◆ samples_radius_

template<typename PointT >

double pcl::SampleConsensusModel< PointT >::samples_radius_

protected

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

Definition at line 568 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< PointT >::drawIndexSampleRadius(), pcl::SampleConsensusModel< PointT >::getSamples(), pcl::SampleConsensusModel< PointT >::getSamplesMaxDist(), and pcl::SampleConsensusModel< PointT >::setSamplesMaxDist().

◆ samples_radius_search_

template<typename PointT >

SearchPtr pcl::SampleConsensusModel< PointT >::samples_radius_search_

protected

The search object for picking subsequent samples using radius search.

Definition at line 571 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< PointT >::drawIndexSampleRadius(), and pcl::SampleConsensusModel< PointT >::setSamplesMaxDist().

◆ shuffled_indices_

template<typename PointT >

Indices 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 574 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< PointT >::drawIndexSample(), pcl::SampleConsensusModel< PointT >::drawIndexSampleRadius(), pcl::SampleConsensusModel< PointT >::setIndices(), and pcl::SampleConsensusModel< PointT >::setInputCloud().

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

pcl/sample_consensus/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

◆ ConstPtr

◆ PointCloud

◆ PointCloudConstPtr

◆ PointCloudPtr

◆ Ptr

◆ SearchPtr

Constructor & Destructor Documentation

◆ SampleConsensusModel() [1/3]

◆ SampleConsensusModel() [2/3]

◆ SampleConsensusModel() [3/3]

◆ ~SampleConsensusModel()

Member Function Documentation

◆ computeModelCoefficients()

◆ computeVariance() [1/2]

◆ computeVariance() [2/2]

◆ countWithinDistance()

◆ doSamplesVerifyModel()

◆ drawIndexSample()

◆ drawIndexSampleRadius()

◆ getClassName()

◆ getDistancesToModel()

◆ getIndices()

◆ getInputCloud()

◆ getModelSize()

◆ getModelType()

◆ getRadiusLimits()

◆ getSamples()

◆ getSampleSize()

◆ getSamplesMaxDist()

◆ isModelValid()

◆ isSampleGood()

◆ optimizeModelCoefficients()

◆ projectPoints()

◆ rnd()

◆ selectWithinDistance()

◆ setIndices() [1/2]

◆ setIndices() [2/2]

◆ setInputCloud()

◆ setModelConstraints()

◆ setRadiusLimits()

◆ setSamplesMaxDist()

Friends And Related Function Documentation

◆ ProgressiveSampleConsensus< PointT >

Member Data Documentation

◆ custom_model_constraints_

◆ error_sqr_dists_

◆ indices_

◆ input_

◆ max_sample_checks_

◆ model_name_

◆ model_size_

◆ radius_max_

◆ radius_min_

◆ rng_alg_

◆ rng_dist_

◆ rng_gen_

◆ sample_size_

◆ samples_radius_

◆ samples_radius_search_

◆ shuffled_indices_

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