A Sample Consensus Model class for determining the 2 perpendicular directions to which most normals align. More...

#include <pcl_sac_model_orientation.h>

Public Types
typedef boost::shared_ptr < const SACModelOrientation >	ConstPtr
typedef SampleConsensusModel < NormalT >::PointCloud	Normals
typedef SampleConsensusModel < NormalT > ::PointCloudConstPtr	NormalsConstPtr
typedef SampleConsensusModel < NormalT >::PointCloudPtr	NormalsPtr
typedef boost::shared_ptr < SACModelOrientation >	Ptr
Public Member Functions
bool	computeModelCoefficients (const std::vector< int > &samples, Eigen::VectorXf &model_coefficients)
	Check whether the given index samples can form a valid model, compute the model coefficients from these samples and store them internally in model_coefficients_.
int	countWithinDistance (const Eigen::VectorXf &model_coefficients, double threshold)
	Count all the points which respect the given model coefficients as inliers.
bool	doSamplesVerifyModel (const std::set< int > &indices, const Eigen::VectorXf &model_coefficients, double threshold)
	Verify whether a subset of indices verifies the internal model coefficients.
Eigen::Vector3f	getAxis () const
	Get the fixed axis.
void	getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector< double > &distances)
	Compute all distances from the cloud data to a given model. -- Not needed.
pcl::SacModel	getModelType () const
	Return an unique id for each type of model employed.
void	getSamples (int &iterations, std::vector< int > &samples)
	Get a random point and return its index.
bool	isSampleGood (const std::vector< int > &samples) const
	Check if a sample of indices results in a good sample of points indices. Pure virtual.
void	optimizeModelCoefficients (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients)
void	projectPoints (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, Normals &projected_points, bool copy_data_fields=true)
	Create a new point cloud with inliers projected onto the model.
void	refitModel (const std::vector< int > &inliers, std::vector< double > &refit_coefficients)
	Recompute the model coefficients using the given inlier set and return them to the user. Pure virtual.
	SACModelOrientation (const NormalsConstPtr &cloud)
	Constructor for base SACModelOrientation.
	SACModelOrientation (const NormalsConstPtr &cloud, const std::vector< int > &indices)
	Constructor for base SACModelOrientation.
void	selectWithinDistance (const Eigen::VectorXf &model_coefficients, double threshold, std::vector< int > &inliers)
	Select all the points which respect the given model coefficients as inliers.
void	setAxis (Eigen::Vector3f axis)
	Specify the fixed "up" axis (the sides will be perpendicular to it).
Public Attributes
Eigen::Vector3f	axis_
	The fixed axis (the sides will be perpendicular to it).
Protected Member Functions
bool	isModelValid (const Eigen::VectorXf &model_coefficients)
	Check whether a model is valid given the user constraints.
Private Attributes
std::vector< int >	back_indices_
std::vector< int >	front_indices_
KdTreeFLANN< NormalT >::Ptr	kdtree_
	Index of the nx channel (the x component of the normal vector). The next indices are assumed to be that of ny and nz!
std::vector< int >	left_indices_
std::vector< float >	points_sqr_distances_
std::vector< int >	right_indices_

Detailed Description

template<typename NormalT>
class pcl::SACModelOrientation< NormalT >

A Sample Consensus Model class for determining the 2 perpendicular directions to which most normals align.

Definition at line 61 of file pcl_sac_model_orientation.h.

Member Typedef Documentation

template<typename NormalT >

typedef boost::shared_ptr<const SACModelOrientation> pcl::SACModelOrientation< NormalT >::ConstPtr

Definition at line 72 of file pcl_sac_model_orientation.h.

template<typename NormalT >

typedef SampleConsensusModel<NormalT>::PointCloud pcl::SACModelOrientation< NormalT >::Normals

Definition at line 67 of file pcl_sac_model_orientation.h.

template<typename NormalT >

typedef SampleConsensusModel<NormalT>::PointCloudConstPtr pcl::SACModelOrientation< NormalT >::NormalsConstPtr

Definition at line 69 of file pcl_sac_model_orientation.h.

template<typename NormalT >

typedef SampleConsensusModel<NormalT>::PointCloudPtr pcl::SACModelOrientation< NormalT >::NormalsPtr

Definition at line 68 of file pcl_sac_model_orientation.h.

template<typename NormalT >

typedef boost::shared_ptr<SACModelOrientation> pcl::SACModelOrientation< NormalT >::Ptr

Definition at line 71 of file pcl_sac_model_orientation.h.

Constructor & Destructor Documentation

template<typename NormalT >

pcl::SACModelOrientation< NormalT >::SACModelOrientation ( const NormalsConstPtr & cloud ) [inline]

Constructor for base SACModelOrientation.

Parameters:

cloud the input point cloud dataset containing the normals

Definition at line 82 of file pcl_sac_model_orientation.h.

template<typename NormalT >

pcl::SACModelOrientation< NormalT >::SACModelOrientation	(	const NormalsConstPtr &	cloud,
		const std::vector< int > &	indices
	)		`[inline]`

Constructor for base SACModelOrientation.

Parameters:

cloud	the input point cloud dataset
indices	a vector of point indices to be used from cloud

Definition at line 95 of file pcl_sac_model_orientation.h.

Member Function Documentation

template<typename NormalT >

bool pcl::SACModelOrientation< NormalT >::computeModelCoefficients	(	const std::vector< int > &	samples,
		Eigen::VectorXf &	model_coefficients
	)

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

Note:: Model coefficients are the normal of the sample point (and it's index for testModelCoefficients)

Parameters:

samples the point indices found as possible good candidates for creating a valid model

Definition at line 90 of file pcl_sac_model_orientation.hpp.

template<typename NormalT >

int pcl::SACModelOrientation< NormalT >::countWithinDistance	(	const Eigen::VectorXf &	model_coefficients,
		double	threshold
	)		`[inline]`

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	a maximum admissible distance threshold for determining the inliers from the outliers

Returns:: the resultant number of inliers

Definition at line 159 of file pcl_sac_model_orientation.h.

template<typename NormalT >

bool pcl::SACModelOrientation< NormalT >::doSamplesVerifyModel	(	const std::set< int > &	indices,
		const Eigen::VectorXf &	model_coefficients,
		double	threshold
	)		`[inline]`

Verify whether a subset of indices verifies the internal model coefficients.

Parameters:

indices	the data indices that need to be tested against the model (each element is an index of indices_)
threshold	a maximum admissible distance threshold for determining the inliers from the outliers

Definition at line 180 of file pcl_sac_model_orientation.h.

template<typename NormalT >

Eigen::Vector3f pcl::SACModelOrientation< NormalT >::getAxis ( ) const [inline]

Get the fixed axis.

Definition at line 109 of file pcl_sac_model_orientation.h.

template<typename NormalT >

void pcl::SACModelOrientation< NormalT >::getDistancesToModel	(	const Eigen::VectorXf &	model_coefficients,
		std::vector< double > &	distances
	)		`[inline]`

Compute all distances from the cloud data to a given model. -- Not needed.

Parameters:

model_coefficients	the coefficients of a model that we need to compute distances to
distances	the resultant estimated distances

Definition at line 139 of file pcl_sac_model_orientation.h.

template<typename NormalT >

pcl::SacModel pcl::SACModelOrientation< NormalT >::getModelType ( ) const [inline]

Return an unique id for each type of model employed.

Definition at line 192 of file pcl_sac_model_orientation.h.

template<typename NormalT >

void pcl::SACModelOrientation< NormalT >::getSamples	(	int &	iterations,
		std::vector< int > &	samples
	)

Get a random point and return its index.

Parameters:

iterations	the internal number of iterations used by SAC methods (incremented at samplings that can not produce a model) -- Not needed.
samples	the resultant model samples

: we get an index of the indices_ vector because normals_ has only those elements!

Definition at line 69 of file pcl_sac_model_orientation.hpp.

template<typename NormalT >

bool pcl::SACModelOrientation< NormalT >::isModelValid ( const Eigen::VectorXf & model_coefficients ) [inline, protected]

Check whether a model is valid given the user constraints.

Parameters:

model_coefficients the set of model coefficients

Definition at line 206 of file pcl_sac_model_orientation.h.

template<typename PointT >

bool pcl::SACModelOrientation< PointT >::isSampleGood ( const std::vector< int > & samples ) const

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

Parameters:

samples the resultant index samples

Definition at line 236 of file pcl_sac_model_orientation.hpp.

template<typename NormalT >

void pcl::SACModelOrientation< NormalT >::optimizeModelCoefficients	(	const std::vector< int > &	inliers,
		const Eigen::VectorXf &	model_coefficients,
		Eigen::VectorXf &	optimized_coefficients
	)		`[inline]`

Definition at line 194 of file pcl_sac_model_orientation.h.

template<typename NormalT >

void pcl::SACModelOrientation< NormalT >::projectPoints	(	const std::vector< int > &	inliers,
		const Eigen::VectorXf &	model_coefficients,
		Normals &	projected_points,
		bool	copy_data_fields = `true`
	)		`[inline]`

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

Parameters:

inliers	the data inliers that we want to project on the model (each element is an index of indices_)
model_coefficients	the coefficients of a model
projected_points	the resultant projected points

Definition at line 172 of file pcl_sac_model_orientation.h.

template<typename NormalT >

void pcl::SACModelOrientation< NormalT >::refitModel	(	const std::vector< int > &	inliers,
		std::vector< double > &	refit_coefficients
	)

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 (eg. after a least-squares optimization)

Parameters:

inliers	the data inliers found as supporting the model (each element is an index of indices_)
refit_coefficients	the resultant recomputed coefficients (has -1 as source index in refit_coefficients[3] at failures)

inliers is a list of indices of the indices_ array! normal_ contains only the elements listed in the indices_ array!

Definition at line 110 of file pcl_sac_model_orientation.hpp.

template<typename NormalT >

void pcl::SACModelOrientation< NormalT >::selectWithinDistance	(	const Eigen::VectorXf &	model_coefficients,
		double	threshold,
		std::vector< int > &	inliers
	)

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

Parameters:

model_coefficients	the coefficients of a model that we need to compute distances to
threshold	a maximum admissible distance threshold for determining the inliers from the outliers
inliers	the resultant model inliers (each element is an index of indices_)