SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation. More...

#include <pcl/segmentation/sac_segmentation.h>

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

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

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Public Types
typedef SACSegmentation < PointT >::PointCloud	PointCloud

typedef PointCloud::Ptr	PointCloudPtr

typedef PointCloud::ConstPtr	PointCloudConstPtr

typedef pcl::PointCloud< PointNT >	PointCloudN

typedef PointCloudN::Ptr	PointCloudNPtr

typedef PointCloudN::ConstPtr	PointCloudNConstPtr

typedef SampleConsensus < PointT >::Ptr	SampleConsensusPtr

typedef SampleConsensusModel < PointT >::Ptr	SampleConsensusModelPtr

typedef SampleConsensusModelFromNormals < PointT, PointNT >::Ptr	SampleConsensusModelFromNormalsPtr

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

typedef PointIndices::Ptr	PointIndicesPtr

typedef PointIndices::ConstPtr	PointIndicesConstPtr

Public Member Functions
	SACSegmentationFromNormals ()
	Empty constructor. 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...

void	setNormalDistanceWeight (double distance_weight)
	Set 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...

double	getNormalDistanceWeight () const
	Get 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...

void	setMinMaxOpeningAngle (const double &min_angle, const double &max_angle)
	Set the minimum opning angle for a cone model. More...

void	getMinMaxOpeningAngle (double &min_angle, double &max_angle)
	Get the opening angle which we need minumum to validate a cone model. More...

void	setDistanceFromOrigin (const double d)
	Set the distance we expect a plane model to be from the origin. More...

double	getDistanceFromOrigin () const
	Get the distance of a plane model from the origin. More...

void	setModelType (int model)
	The type of model to use (user given parameter). More...

int	getModelType () const
	Get the type of SAC model used. More...

SampleConsensusPtr	getMethod () const
	Get a pointer to the SAC method used. More...

SampleConsensusModelPtr	getModel () const
	Get a pointer to the SAC model used. More...

void	setMethodType (int method)
	The type of sample consensus method to use (user given parameter). More...

int	getMethodType () const
	Get the type of sample consensus method used. More...

void	setDistanceThreshold (double threshold)
	Distance to the model threshold (user given parameter). More...

double	getDistanceThreshold () const
	Get the distance to the model threshold. More...

void	setMaxIterations (int max_iterations)
	Set the maximum number of iterations before giving up. More...

int	getMaxIterations () const
	Get maximum number of iterations before giving up. More...

void	setProbability (double probability)
	Set the probability of choosing at least one sample free from outliers. More...

double	getProbability () const
	Get the probability of choosing at least one sample free from outliers. More...

void	setOptimizeCoefficients (bool optimize)
	Set to true if a coefficient refinement is required. More...

bool	getOptimizeCoefficients () const
	Get the coefficient refinement internal flag. 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)
	Get the minimum and maximum allowable radius limits for the model as set by the user. More...

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

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

void	setAxis (const Eigen::Vector3f &ax)
	Set the axis along which we need to search for a model perpendicular to. More...

Eigen::Vector3f	getAxis () const
	Get the axis along which we need to search for a model perpendicular to. More...

void	setEpsAngle (double ea)
	Set the angle epsilon (delta) threshold. More...

double	getEpsAngle () const
	Get the epsilon (delta) model angle threshold in radians. More...

virtual void	segment (PointIndices &inliers, ModelCoefficients &model_coefficients)
	Base method for segmentation of a model in a PointCloud given by <setInputCloud (), setIndices ()> More...

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

PointCloudConstPtr const	getInputCloud ()
	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 IndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...

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

void	setIndices (size_t row_start, size_t col_start, size_t nb_rows, size_t nb_cols)
	Set the indices for the points laying within an interest region of the point cloud. More...

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

const PointT &	operator[] (size_t pos)
	Override PointCloud operator[] to shorten code. More...

Detailed Description

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

SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation.

Definition at line 294 of file sac_segmentation.h.

Member Typedef Documentation

template<typename PointT , typename PointNT >

typedef SACSegmentation<PointT>::PointCloud pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloud

Definition at line 307 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

typedef PointCloud::ConstPtr pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloudConstPtr

Definition at line 309 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

typedef pcl::PointCloud<PointNT> pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloudN

Definition at line 311 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

typedef PointCloudN::ConstPtr pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloudNConstPtr

Definition at line 313 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

typedef PointCloudN::Ptr pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloudNPtr

Definition at line 312 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

typedef PointCloud::Ptr pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloudPtr

Definition at line 308 of file sac_segmentation.h.

template<typename PointT>

typedef PointIndices::ConstPtr pcl::PCLBase< PointT >::PointIndicesConstPtr

inherited

Definition at line 79 of file pcl_base.h.

template<typename PointT>

typedef PointIndices::Ptr pcl::PCLBase< PointT >::PointIndicesPtr

inherited

Definition at line 78 of file pcl_base.h.

template<typename PointT , typename PointNT >

typedef SampleConsensusModelFromNormals<PointT, PointNT>::Ptr pcl::SACSegmentationFromNormals< PointT, PointNT >::SampleConsensusModelFromNormalsPtr

Definition at line 317 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

typedef SampleConsensusModel<PointT>::Ptr pcl::SACSegmentationFromNormals< PointT, PointNT >::SampleConsensusModelPtr

Definition at line 316 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

typedef SampleConsensus<PointT>::Ptr pcl::SACSegmentationFromNormals< PointT, PointNT >::SampleConsensusPtr

Definition at line 315 of file sac_segmentation.h.

template<typename PointT>

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

inherited

Definition at line 77 of file sac_segmentation.h.

Constructor & Destructor Documentation

template<typename PointT , typename PointNT >

pcl::SACSegmentationFromNormals< PointT, PointNT >::SACSegmentationFromNormals ( )

inline

Empty constructor.

Definition at line 320 of file sac_segmentation.h.

Member Function Documentation

template<typename PointT>

Eigen::Vector3f pcl::SACSegmentation< PointT >::getAxis ( ) const

inlineinherited

Get the axis along which we need to search for a model perpendicular to.

Definition at line 213 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

double pcl::SACSegmentationFromNormals< PointT, PointNT >::getDistanceFromOrigin ( ) const

inline

Get the distance of a plane model from the origin.

Definition at line 377 of file sac_segmentation.h.

template<typename PointT>

double pcl::SACSegmentation< PointT >::getDistanceThreshold ( ) const

inlineinherited

Get the distance to the model threshold.

Definition at line 130 of file sac_segmentation.h.

template<typename PointT>

double pcl::SACSegmentation< PointT >::getEpsAngle ( ) const

inlineinherited

Get the epsilon (delta) model angle threshold in radians.

Definition at line 223 of file sac_segmentation.h.

template<typename PointT>

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

inlineinherited

Get a pointer to the vector of indices used.

Definition at line 190 of file pcl_base.h.

template<typename PointT>

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

inlineinherited

Get a pointer to the input point cloud dataset.

Definition at line 107 of file pcl_base.h.

template<typename PointT , typename PointNT >

PointCloudNConstPtr pcl::SACSegmentationFromNormals< PointT, PointNT >::getInputNormals ( ) const

inline

Get a pointer to the normals of the input XYZ point cloud dataset.

Definition at line 337 of file sac_segmentation.h.

template<typename PointT>

int pcl::SACSegmentation< PointT >::getMaxIterations ( ) const

inlineinherited

Get maximum number of iterations before giving up.

Definition at line 140 of file sac_segmentation.h.

template<typename PointT>

SampleConsensusPtr pcl::SACSegmentation< PointT >::getMethod ( ) const

inlineinherited

Get a pointer to the SAC method used.

Definition at line 106 of file sac_segmentation.h.

template<typename PointT>

int pcl::SACSegmentation< PointT >::getMethodType ( ) const

inlineinherited

Get the type of sample consensus method used.

Definition at line 120 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

void pcl::SACSegmentationFromNormals< PointT, PointNT >::getMinMaxOpeningAngle	(	double &	min_angle,
		double &	max_angle
	)

inline

Get the opening angle which we need minumum to validate a cone model.

Definition at line 363 of file sac_segmentation.h.

template<typename PointT>

SampleConsensusModelPtr pcl::SACSegmentation< PointT >::getModel ( ) const

inlineinherited

Get a pointer to the SAC model used.

Definition at line 110 of file sac_segmentation.h.

template<typename PointT>

int pcl::SACSegmentation< PointT >::getModelType ( ) const

inlineinherited

Get the type of SAC model used.

Definition at line 102 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

double pcl::SACSegmentationFromNormals< PointT, PointNT >::getNormalDistanceWeight ( ) const

inline

Get the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal.

Definition at line 349 of file sac_segmentation.h.

template<typename PointT>

bool pcl::SACSegmentation< PointT >::getOptimizeCoefficients ( ) const

inlineinherited

Get the coefficient refinement internal flag.

Definition at line 160 of file sac_segmentation.h.

template<typename PointT>

double pcl::SACSegmentation< PointT >::getProbability ( ) const

inlineinherited

Get the probability of choosing at least one sample free from outliers.

Definition at line 150 of file sac_segmentation.h.

template<typename PointT>

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

inlineinherited

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 179 of file sac_segmentation.h.

template<typename PointT>

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

inlineinherited

Get maximum distance allowed when drawing random samples.

Parameters

[out] radius the maximum distance (L2 norm)

Definition at line 200 of file sac_segmentation.h.

template<typename PointT>

const PointT& pcl::PCLBase< PointT >::operator[] ( size_t pos)

inlineinherited

Override PointCloud operator[] to shorten code.

Note: this method can be called instead of (*input_)[(*indices_)[pos]] or input_->points[(*indices_)[pos]]

Parameters

pos	position in indices_ vector

Definition at line 197 of file pcl_base.h.

template<typename PointT >

void pcl::SACSegmentation< PointT >::segment	(	PointIndices &	inliers,
		ModelCoefficients &	model_coefficients
	)

virtualinherited

Base method for segmentation of a model in a PointCloud given by <setInputCloud (), setIndices ()>

Parameters

[in]	inliers	the resultant point indices that support the model found (inliers)
[out]	model_coefficients	the resultant model coefficients

Definition at line 71 of file sac_segmentation.hpp.

template<typename PointT>

void pcl::SACSegmentation< PointT >::setAxis ( const Eigen::Vector3f & ax)

inlineinherited

Set the axis along which we need to search for a model perpendicular to.

Parameters

[in] ax the axis along which we need to search for a model perpendicular to

Definition at line 209 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

void pcl::SACSegmentationFromNormals< PointT, PointNT >::setDistanceFromOrigin ( const double d)

inline

Set the distance we expect a plane model to be from the origin.

Parameters

[in] d distance from the template plane modl to the origin

Definition at line 373 of file sac_segmentation.h.

template<typename PointT>

void pcl::SACSegmentation< PointT >::setDistanceThreshold ( double threshold)

inlineinherited

Distance to the model threshold (user given parameter).

Parameters

[in] threshold the distance threshold to use

Definition at line 126 of file sac_segmentation.h.

template<typename PointT>

void pcl::SACSegmentation< PointT >::setEpsAngle ( double ea)

inlineinherited

Set the angle epsilon (delta) threshold.

Parameters

[in] ea the maximum allowed difference between the model normal and the given axis in radians.

Definition at line 219 of file sac_segmentation.h.

template<typename PointT>

void pcl::PCLBase< PointT >::setIndices ( const IndicesPtr & indices)

inlineinherited

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

Parameters

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

Definition at line 113 of file pcl_base.h.

template<typename PointT>

void pcl::PCLBase< PointT >::setIndices ( const IndicesConstPtr & indices)

inlineinherited

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

Parameters

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

Definition at line 124 of file pcl_base.h.

template<typename PointT>

void pcl::PCLBase< PointT >::setIndices ( const PointIndicesConstPtr & indices)

inlineinherited

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

Parameters

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

Definition at line 135 of file pcl_base.h.

template<typename PointT>

void pcl::PCLBase< PointT >::setIndices	(	size_t	row_start,
		size_t	col_start,
		size_t	nb_rows,
		size_t	nb_cols
	)

inlineinherited

Set the indices for the points laying within an interest region of the point cloud.

Note: you shouldn't call this method on unorganized point clouds!

Parameters

row_start	the offset on rows
col_start	the offset on columns
nb_rows	the number of rows to be considered row_start included
nb_cols	the number of columns to be considered col_start included

Definition at line 151 of file pcl_base.h.

template<typename PointT>

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

inlinevirtualinherited

Provide a pointer to the input dataset.

Parameters

cloud the const boost shared pointer to a PointCloud message

Reimplemented in pcl::PCA< PointT >.

Definition at line 103 of file pcl_base.h.

template<typename PointT , typename PointNT >

void pcl::SACSegmentationFromNormals< PointT, PointNT >::setInputNormals ( const PointCloudNConstPtr & normals)

inline

Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.

Parameters

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

Definition at line 333 of file sac_segmentation.h.

template<typename PointT>

void pcl::SACSegmentation< PointT >::setMaxIterations ( int max_iterations)

inlineinherited

Set the maximum number of iterations before giving up.

Parameters

[in] max_iterations the maximum number of iterations the sample consensus method will run

Definition at line 136 of file sac_segmentation.h.

template<typename PointT>

void pcl::SACSegmentation< PointT >::setMethodType ( int method)

inlineinherited

The type of sample consensus method to use (user given parameter).

Parameters

[in] method the method type (check method_types.h)

Definition at line 116 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

void pcl::SACSegmentationFromNormals< PointT, PointNT >::setMinMaxOpeningAngle	(	const double &	min_angle,
		const double &	max_angle
	)

inline

Set the minimum opning angle for a cone model.

Parameters

oa	the opening angle which we need minumum to validate a cone model.

Definition at line 355 of file sac_segmentation.h.

template<typename PointT>

void pcl::SACSegmentation< PointT >::setModelType ( int model)

inlineinherited

The type of model to use (user given parameter).

Parameters

[in] model the model type (check model_types.h)

Definition at line 98 of file sac_segmentation.h.

template<typename PointT , typename PointNT >

void pcl::SACSegmentationFromNormals< PointT, PointNT >::setNormalDistanceWeight ( double distance_weight)

inline

Set the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal.

Parameters

[in] distance_weight the distance/angular weight

Definition at line 344 of file sac_segmentation.h.

template<typename PointT>

void pcl::SACSegmentation< PointT >::setOptimizeCoefficients ( bool optimize)

inlineinherited

Set to true if a coefficient refinement is required.

Parameters

[in] optimize true for enabling model coefficient refinement, false otherwise

Definition at line 156 of file sac_segmentation.h.

template<typename PointT>

void pcl::SACSegmentation< PointT >::setProbability ( double probability)

inlineinherited

Set the probability of choosing at least one sample free from outliers.

Parameters

[in] probability the model fitting probability

Definition at line 146 of file sac_segmentation.h.

template<typename PointT>

void pcl::SACSegmentation< PointT >::setRadiusLimits	(	const double &	min_radius,
		const double &	max_radius
	)

inlineinherited

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

Definition at line 168 of file sac_segmentation.h.

template<typename PointT>

void pcl::SACSegmentation< PointT >::setSamplesMaxDist	(	const double &	radius,
		SearchPtr	search
	)

inlineinherited

Set the maximum distance allowed when drawing random samples.

Parameters

[in] radius the maximum distance (L2 norm)

Definition at line 189 of file sac_segmentation.h.

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

/builddir/build/BUILD/PCL-1.6.0-Source/segmentation/include/pcl/segmentation/sac_segmentation.h
/builddir/build/BUILD/PCL-1.6.0-Source/segmentation/include/pcl/segmentation/impl/sac_segmentation.hpp

Public Types

Public Member Functions

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

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