Point Cloud Library (PCL): pcl::SampleConsensusModelTorus< PointT, PointNT

SampleConsensusModelTorus defines a model for 3D torus segmentation. More...

#include <pcl/sample_consensus/sac_model_torus.h>

Inheritance diagram for pcl::SampleConsensusModelTorus< PointT, PointNT >:

Collaboration diagram for pcl::SampleConsensusModelTorus< PointT, PointNT >:

Public Types
using	Ptr = shared_ptr< SampleConsensusModelTorus< PointT, PointNT > >

using	ConstPtr = shared_ptr< const SampleConsensusModelTorus< PointT, PointNT > >

Public Types inherited from pcl::SampleConsensusModel< PointT >
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 Types inherited from pcl::SampleConsensusModelFromNormals< PointT, PointNT >
using	PointCloudNConstPtr = typename pcl::PointCloud< PointNT >::ConstPtr

using	PointCloudNPtr = typename pcl::PointCloud< PointNT >::Ptr

using	Ptr = shared_ptr< SampleConsensusModelFromNormals< PointT, PointNT > >

using	ConstPtr = shared_ptr< const SampleConsensusModelFromNormals< PointT, PointNT > >

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

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

	SampleConsensusModelTorus (const SampleConsensusModelTorus &source)
	Copy constructor. More...

	~SampleConsensusModelTorus () override=default
	Empty destructor. More...

SampleConsensusModelTorus &	operator= (const SampleConsensusModelTorus &source)
	Copy constructor. More...

bool	computeModelCoefficients (const Indices &samples, Eigen::VectorXf &model_coefficients) const override
	Check whether the given index samples can form a valid torus model, compute the model coefficients from these samples and store them in model_coefficients. More...

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

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

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

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

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

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

pcl::SacModel	getModelType () const override
	Return a unique id for this model (SACMODEL_TORUS). More...

Public Member Functions inherited from pcl::SampleConsensusModel< PointT >
	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 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...

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...

Public Member Functions inherited from pcl::SampleConsensusModelFromNormals< PointT, PointNT >
	SampleConsensusModelFromNormals ()
	Empty constructor for base SampleConsensusModelFromNormals. More...

virtual	~SampleConsensusModelFromNormals ()=default
	Destructor. More...

void	setNormalDistanceWeight (const double w)
	Set the normal angular distance weight. More...

double	getNormalDistanceWeight () const
	Get the normal angular distance weight. More...

void	setInputNormals (const PointCloudNConstPtr &normals)
	Provide a pointer to the input dataset that contains the point normals of the XYZ dataset. More...

PointCloudNConstPtr	getInputNormals () const
	Get a pointer to the normals of the input XYZ point cloud dataset. More...

Protected Member Functions
void	projectPointToTorus (const Eigen::Vector3f &pt, const Eigen::Vector3f &pt_n, const Eigen::VectorXf &model_coefficients, Eigen::Vector3f &pt_proj) const
	Project a point onto a torus given by its model coefficients (radii, torus_center_point, torus_normal) More...

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

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

Protected Member Functions inherited from pcl::SampleConsensusModel< PointT >
	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...

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

Additional Inherited Members
Protected Attributes inherited from pcl::SampleConsensusModel< PointT >
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...

Protected Attributes inherited from pcl::SampleConsensusModelFromNormals< PointT, PointNT >
double	normal_distance_weight_ {0.0}
	The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. More...

PointCloudNConstPtr	normals_
	A pointer to the input dataset that contains the point normals of the XYZ dataset. More...

Static Protected Attributes inherited from pcl::SampleConsensusModel< PointT >
static const unsigned int	max_sample_checks_ = 1000
	The maximum number of samples to try until we get a good one. More...

Detailed Description

template<typename PointT, typename PointNT>
class pcl::SampleConsensusModelTorus< PointT, PointNT >

SampleConsensusModelTorus defines a model for 3D torus segmentation.

The model coefficients are defined as:

radii.inner : the torus's inner radius
radii.outer : the torus's outer radius
torus_center_point.x : the X coordinate of the center of the torus
torus_center_point.y : the Y coordinate of the center of the torus
torus_center_point.z : the Z coordinate of the center of the torus
torus_normal.x : the X coordinate of the normal of the torus
torus_normal.y : the Y coordinate of the normal of the torus
torus_normal.z : the Z coordinate of the normal of the torus

Author: lasdasdas

Definition at line 64 of file sac_model_torus.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointT , typename PointNT >

using pcl::SampleConsensusModelTorus< PointT, PointNT >::ConstPtr = shared_ptr<const SampleConsensusModelTorus<PointT, PointNT> >

Definition at line 82 of file sac_model_torus.h.

◆ Ptr

template<typename PointT , typename PointNT >

using pcl::SampleConsensusModelTorus< PointT, PointNT >::Ptr = shared_ptr<SampleConsensusModelTorus<PointT, PointNT> >

Definition at line 81 of file sac_model_torus.h.

Constructor & Destructor Documentation

◆ SampleConsensusModelTorus() [1/3]

template<typename PointT , typename PointNT >

pcl::SampleConsensusModelTorus< PointT, PointNT >::SampleConsensusModelTorus	(	const PointCloudConstPtr &	cloud,
		bool	random = `false`
	)

inline

Constructor for base SampleConsensusModelTorus.

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 89 of file sac_model_torus.h.

References pcl::SampleConsensusModel< PointT >::model_name_, pcl::SampleConsensusModel< PointT >::model_size_, and pcl::SampleConsensusModel< PointT >::sample_size_.

◆ SampleConsensusModelTorus() [2/3]

template<typename PointT , typename PointNT >

pcl::SampleConsensusModelTorus< PointT, PointNT >::SampleConsensusModelTorus	(	const PointCloudConstPtr &	cloud,
		const Indices &	indices,
		bool	random = `false`
	)

inline

Constructor for base SampleConsensusModelTorus.

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 104 of file sac_model_torus.h.

References pcl::SampleConsensusModel< PointT >::model_name_, pcl::SampleConsensusModel< PointT >::model_size_, and pcl::SampleConsensusModel< PointT >::sample_size_.

◆ SampleConsensusModelTorus() [3/3]

template<typename PointT , typename PointNT >

pcl::SampleConsensusModelTorus< PointT, PointNT >::SampleConsensusModelTorus ( const SampleConsensusModelTorus< PointT, PointNT > & source )

inline

Copy constructor.

Parameters

[in] source the model to copy into this

Definition at line 118 of file sac_model_torus.h.

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

◆ ~SampleConsensusModelTorus()

template<typename PointT , typename PointNT >

pcl::SampleConsensusModelTorus< PointT, PointNT >::~SampleConsensusModelTorus ( )

overridedefault

Empty destructor.

Member Function Documentation

◆ computeModelCoefficients()

template<typename PointT , typename PointNT >

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

overridevirtual

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

The torus coefficients are: radii, torus_center_point, torus_normal.

Parameters

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

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 97 of file sac_model_torus.hpp.

◆ countWithinDistance()

template<typename PointT , typename PointNT >

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

overridevirtual

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

Parameters

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

Returns: the resultant number of inliers

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 332 of file sac_model_torus.hpp.

References pcl::geometry::distance().

◆ doSamplesVerifyModel()

template<typename PointT , typename PointNT >

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

overridevirtual

Verify whether a subset of indices verifies the given torus model coefficients.

Parameters

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

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 529 of file sac_model_torus.hpp.

◆ getDistancesToModel()

template<typename PointT , typename PointNT >

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

overridevirtual

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

Parameters

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

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 271 of file sac_model_torus.hpp.

◆ getModelType()

template<typename PointT , typename PointNT >

pcl::SacModel pcl::SampleConsensusModelTorus< PointT, PointNT >::getModelType ( ) const

inlineoverridevirtual

Return a unique id for this model (SACMODEL_TORUS).

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 215 of file sac_model_torus.h.

References pcl::SACMODEL_TORUS.

◆ isModelValid()

template<typename PointT , typename PointNT >

bool pcl::SampleConsensusModelTorus< PointT, PointNT >::isModelValid ( const Eigen::VectorXf & model_coefficients ) const

overrideprotectedvirtual

Check whether a model is valid given the user constraints.

Parameters

[in] model_coefficients the set of model coefficients

Reimplemented from pcl::SampleConsensusModel< PointT >.

Definition at line 549 of file sac_model_torus.hpp.

◆ isSampleGood()

template<typename PointT , typename PointNT >

bool pcl::SampleConsensusModelTorus< PointT, PointNT >::isSampleGood ( const Indices & samples ) const

overrideprotectedvirtual

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

Pure virtual.

Parameters

[in] samples the resultant index samples

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 53 of file sac_model_torus.hpp.

◆ operator=()

template<typename PointT , typename PointNT >

SampleConsensusModelTorus& pcl::SampleConsensusModelTorus< PointT, PointNT >::operator= ( const SampleConsensusModelTorus< PointT, PointNT > & source )

inline

Copy constructor.

Parameters

[in] source the model to copy into this

Definition at line 132 of file sac_model_torus.h.

◆ optimizeModelCoefficients()

template<typename PointT , typename PointNT >

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

overridevirtual

Recompute the torus coefficients using the given inlier set and return them to the user.

Parameters

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

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 359 of file sac_model_torus.hpp.

◆ projectPoints()

template<typename PointT , typename PointNT >

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

overridevirtual

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

Parameters

[in]	inliers	the data inliers that we want to project on the torus model
[in]	model_coefficients	the coefficients of a torus model
[out]	projected_points	the resultant projected points
[in]	copy_data_fields	set to true if we need to copy the other data fields

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 466 of file sac_model_torus.hpp.

References pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::resize(), and pcl::PointCloud< PointT >::width.

◆ projectPointToTorus()

template<typename PointT , typename PointNT >

void pcl::SampleConsensusModelTorus< PointT, PointNT >::projectPointToTorus	(	const Eigen::Vector3f &	pt,
		const Eigen::Vector3f &	pt_n,
		const Eigen::VectorXf &	model_coefficients,
		Eigen::Vector3f &	pt_proj
	)		const

protected

Project a point onto a torus given by its model coefficients (radii, torus_center_point, torus_normal)

Parameters

[in]	pt	the input point to project
[in]	model_coefficients	the coefficients of the torus (radii, torus_center_point, torus_normal)
[out]	pt_proj	the resultant projected point

Definition at line 407 of file sac_model_torus.hpp.

◆ selectWithinDistance()

template<typename PointT , typename PointNT >

void pcl::SampleConsensusModelTorus< PointT, PointNT >::selectWithinDistance	(	const Eigen::VectorXf &	model_coefficients,
		const double	threshold,
		Indices &	inliers
	)

overridevirtual

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

Parameters

[in]	model_coefficients	the coefficients of a torus 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

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 298 of file sac_model_torus.hpp.

References pcl::geometry::distance().

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

pcl/sample_consensus/sac_model_torus.h
pcl/sample_consensus/impl/sac_model_torus.hpp

Public Types

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

template<typename PointT, typename PointNT> class pcl::SampleConsensusModelTorus< PointT, PointNT >

Member Typedef Documentation

◆ ConstPtr

◆ Ptr

Constructor & Destructor Documentation

◆ SampleConsensusModelTorus() [1/3]

◆ SampleConsensusModelTorus() [2/3]

◆ SampleConsensusModelTorus() [3/3]

◆ ~SampleConsensusModelTorus()

Member Function Documentation

◆ computeModelCoefficients()

◆ countWithinDistance()

◆ doSamplesVerifyModel()

◆ getDistancesToModel()

◆ getModelType()

◆ isModelValid()

◆ isSampleGood()

◆ operator=()

◆ optimizeModelCoefficients()

◆ projectPoints()

◆ projectPointToTorus()

◆ selectWithinDistance()

template<typename PointT, typename PointNT>
class pcl::SampleConsensusModelTorus< PointT, PointNT >