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.
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.
void	getSamples (int &iterations, std::vector< int > &samples)
	Get a set of random data samples and return them as point indices. Pure virtual.
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
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 Bogdan Rusu

Definition at line 65 of file sac_model.h.

Member Typedef Documentation

template<typename PointT>

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

Definition at line 74 of file sac_model.h.

template<typename PointT>

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

Definition at line 68 of file sac_model.h.

template<typename PointT>

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

Definition at line 69 of file sac_model.h.

template<typename PointT>

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

Definition at line 70 of file sac_model.h.

template<typename PointT>

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

Definition at line 73 of file sac_model.h.

template<typename PointT>

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

Definition at line 71 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 80 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 103 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 129 of file sac_model.h.

template<typename PointT>

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

Destructor for base SampleConsensusModel.

Definition at line 155 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::SampleConsensusModelStick< PointT >, and pcl::SampleConsensusModelLine< PointT >.

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::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 396 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 413 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 327 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 303 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 363 of file sac_model.h.

template<typename PointT>

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

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

Parameters:

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

Definition at line 163 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 335 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 384 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::SampleConsensusModelCylinder< PointT, PointNT >, pcl::SampleConsensusModelCone< PointT, PointNT >, pcl::SampleConsensusModelPlane< PointT >, pcl::SampleConsensusModelRegistration< PointT >, pcl::SampleConsensusModelSphere< PointT >, pcl::SampleConsensusModelCircle2D< PointT >, pcl::SampleConsensusModelStick< PointT >, and pcl::SampleConsensusModelLine< 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::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::SampleConsensusModelStick< PointT >, and pcl::SampleConsensusModelLine< PointT >.

template<typename PointT>

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

Boost-based random number generator.

Definition at line 491 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 309 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 319 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 286 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 350 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 373 of file sac_model.h.

Friends And Related Function Documentation

template<typename PointT>

friend class ProgressiveSampleConsensus< PointT > [friend]

Definition at line 389 of file sac_model.h.

Member Data Documentation

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 461 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 458 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 464 of file sac_model.h.

template<typename PointT>

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

Definition at line 469 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 469 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 481 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 484 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 487 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 472 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 475 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 478 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 >