SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...

#include <pcl/sample_consensus/sac_model_normal_plane.h>

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

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

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List of all members.

Public Types
typedef SampleConsensusModel < PointT >::PointCloud	PointCloud
typedef SampleConsensusModel < PointT >::PointCloudPtr	PointCloudPtr
typedef SampleConsensusModel < PointT >::PointCloudConstPtr	PointCloudConstPtr
typedef SampleConsensusModelFromNormals < PointT, PointNT > ::PointCloudNPtr	PointCloudNPtr
typedef SampleConsensusModelFromNormals < PointT, PointNT > ::PointCloudNConstPtr	PointCloudNConstPtr
typedef boost::shared_ptr < SampleConsensusModelNormalPlane >	Ptr
typedef pcl::search::Search < PointT >::Ptr	SearchPtr
typedef boost::shared_ptr < const SampleConsensusModel >	ConstPtr
typedef boost::shared_ptr < const SampleConsensusModelFromNormals >	ConstPtr
Public Member Functions
	SampleConsensusModelNormalPlane (const PointCloudConstPtr &cloud)
	Constructor for base SampleConsensusModelNormalPlane.
	SampleConsensusModelNormalPlane (const PointCloudConstPtr &cloud, const std::vector< int > &indices)
	Constructor for base SampleConsensusModelNormalPlane.
void	selectWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold, std::vector< int > &inliers)
	Select all the points which respect the given model coefficients as inliers.
virtual int	countWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold)
	Count all the points which respect the given model coefficients as inliers.
void	getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector< double > &distances)
	Compute all distances from the cloud data to a given plane model.
pcl::SacModel	getModelType () const
	Return an unique id for this model (SACMODEL_NORMAL_PLANE).
bool	computeModelCoefficients (const std::vector< int > &samples, Eigen::VectorXf &model_coefficients)
	Check whether the given index samples can form a valid plane model, compute the model coefficients from these samples and store them internally in model_coefficients_.
void	optimizeModelCoefficients (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients)
	Recompute the plane coefficients using the given inlier set and return them to the user.
void	projectPoints (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true)
	Create a new point cloud with inliers projected onto the plane model.
bool	doSamplesVerifyModel (const std::set< int > &indices, const Eigen::VectorXf &model_coefficients, const double threshold)
	Verify whether a subset of indices verifies the given plane model coefficients.
void	getSamples (int &iterations, std::vector< int > &samples)
	Get a set of random data samples and return them as point indices.
virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset.
PointCloudConstPtr	getInputCloud () const
	Get a pointer to the input point cloud dataset.
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.
boost::shared_ptr< std::vector < int > >	getIndices () const
	Get a pointer to the vector of indices used.
unsigned int	getSampleSize () const
	Return the size of a sample from which a model is computed.
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	getRadiusLimits (double &min_radius, double &max_radius)
	Get the minimum and maximum allowable radius limits for the model as set by the user.
void	setSamplesMaxDist (const double &radius, SearchPtr search)
	Set the maximum distance allowed when drawing random samples.
void	getSamplesMaxDist (double &radius)
	Get maximum distance allowed when drawing random samples.
void	setNormalDistanceWeight (const double w)
	Set the normal angular distance weight.
double	getNormalDistanceWeight ()
	Get the normal angular distance weight.
void	setInputNormals (const PointCloudNConstPtr &normals)
	Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.
PointCloudNConstPtr	getInputNormals ()
	Get a pointer to the normals of the input XYZ point cloud dataset.
Friends
class	ProgressiveSampleConsensus< PointT >

Detailed Description

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

SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints.

Basically this means that checking for inliers will not only involve a "distance to model" criterion, but also an additional "maximum angular deviation" between the plane's normal and the inlier points normals.

The model coefficients are defined as:

a : the X coordinate of the plane's normal (normalized)
b : the Y coordinate of the plane's normal (normalized)
c : the Z coordinate of the plane's normal (normalized)
d : the fourth Hessian component of the plane's equation

To set the influence of the surface normals in the inlier estimation process, set the normal weight (0.0-1.0), e.g.:

 SampleConsensusModelNormalPlane<pcl::PointXYZ, pcl::Normal> sac_model;
 ...
 sac_model.setNormalDistanceWeight (0.1);
 ...

Author:: Radu B. Rusu and Jared Glover

Definition at line 75 of file sac_model_normal_plane.h.

Member Typedef Documentation

template<typename PointT>

typedef boost::shared_ptr<const SampleConsensusModel> pcl::SampleConsensusModel< PointT >::ConstPtr [inherited]

Definition at line 74 of file sac_model.h.

template<typename PointT, typename PointNT>

typedef boost::shared_ptr<const SampleConsensusModelFromNormals> pcl::SampleConsensusModelFromNormals< PointT, PointNT >::ConstPtr [inherited]

Definition at line 510 of file sac_model.h.

template<typename PointT , typename PointNT >

typedef SampleConsensusModel<PointT>::PointCloud pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::PointCloud

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 84 of file sac_model_normal_plane.h.

template<typename PointT , typename PointNT >

typedef SampleConsensusModel<PointT>::PointCloudConstPtr pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::PointCloudConstPtr

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 86 of file sac_model_normal_plane.h.

template<typename PointT , typename PointNT >

typedef SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNConstPtr pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::PointCloudNConstPtr

Reimplemented from pcl::SampleConsensusModelFromNormals< PointT, PointNT >.

Definition at line 89 of file sac_model_normal_plane.h.

template<typename PointT , typename PointNT >

typedef SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNPtr pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::PointCloudNPtr

Reimplemented from pcl::SampleConsensusModelFromNormals< PointT, PointNT >.

Definition at line 88 of file sac_model_normal_plane.h.

template<typename PointT , typename PointNT >

typedef SampleConsensusModel<PointT>::PointCloudPtr pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::PointCloudPtr

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 85 of file sac_model_normal_plane.h.

template<typename PointT , typename PointNT >

typedef boost::shared_ptr<SampleConsensusModelNormalPlane> pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::Ptr

Reimplemented from pcl::SampleConsensusModelFromNormals< PointT, PointNT >.

Definition at line 91 of file sac_model_normal_plane.h.

template<typename PointT>

typedef pcl::search::Search<PointT>::Ptr pcl::SampleConsensusModel< PointT >::SearchPtr [inherited]

Definition at line 71 of file sac_model.h.

Constructor & Destructor Documentation

template<typename PointT , typename PointNT >

pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::SampleConsensusModelNormalPlane ( const PointCloudConstPtr & cloud ) [inline]

Constructor for base SampleConsensusModelNormalPlane.

Parameters:

[in] cloud the input point cloud dataset

Definition at line 96 of file sac_model_normal_plane.h.

template<typename PointT , typename PointNT >

pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::SampleConsensusModelNormalPlane	(	const PointCloudConstPtr &	cloud,
		const std::vector< int > &	indices
	)		`[inline]`

Constructor for base SampleConsensusModelNormalPlane.

Parameters:

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

Definition at line 104 of file sac_model_normal_plane.h.

Member Function Documentation

template<typename PointT >

bool pcl::SampleConsensusModelPlane< PointT >::computeModelCoefficients	(	const std::vector< int > &	samples,
		Eigen::VectorXf &	model_coefficients
	)		`[virtual, inherited]`

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

The plane coefficients are: a, b, c, d (ax+by+cz+d=0)

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 65 of file sac_model_plane.hpp.

template<typename PointT , typename PointNT >

int pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::countWithinDistance	(	const Eigen::VectorXf &	model_coefficients,
		const double	threshold
	)		`[virtual]`

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

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 93 of file sac_model_normal_plane.hpp.

template<typename PointT >

bool pcl::SampleConsensusModelPlane< PointT >::doSamplesVerifyModel	(	const std::set< int > &	indices,
		const Eigen::VectorXf &	model_coefficients,
		const double	threshold
	)		`[virtual, inherited]`

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

Parameters:

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

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 329 of file sac_model_plane.hpp.

template<typename PointT , typename PointNT >

void pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::getDistancesToModel	(	const Eigen::VectorXf &	model_coefficients,
		std::vector< double > &	distances
	)		`[virtual]`

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

Parameters:

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

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 133 of file sac_model_normal_plane.hpp.

template<typename PointT>

boost::shared_ptr<std::vector<int> > pcl::SampleConsensusModel< PointT >::getIndices ( ) const [inline, inherited]

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, inherited]

Get a pointer to the input point cloud dataset.

Definition at line 303 of file sac_model.h.

template<typename PointT, typename PointNT>

PointCloudNConstPtr pcl::SampleConsensusModelFromNormals< PointT, PointNT >::getInputNormals ( ) [inline, inherited]

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

Definition at line 546 of file sac_model.h.

template<typename PointT , typename PointNT >

pcl::SacModel pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::getModelType ( ) const [inline, virtual]

Return an unique id for this model (SACMODEL_NORMAL_PLANE).

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 138 of file sac_model_normal_plane.h.

template<typename PointT, typename PointNT>

double pcl::SampleConsensusModelFromNormals< PointT, PointNT >::getNormalDistanceWeight ( ) [inline, inherited]

Get the normal angular distance weight.

Definition at line 531 of file sac_model.h.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::getRadiusLimits	(	double &	min_radius,
		double &	max_radius
	)		`[inline, inherited]`

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, inherited]`

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, inherited]

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, inherited]

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 >

void pcl::SampleConsensusModelPlane< PointT >::optimizeModelCoefficients	(	const std::vector< int > &	inliers,
		const Eigen::VectorXf &	model_coefficients,
		Eigen::VectorXf &	optimized_coefficients
	)		`[virtual, inherited]`

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

Note:: : these are the coefficients of the plane model after refinement (eg. after SVD)

Parameters:

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

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 202 of file sac_model_plane.hpp.

template<typename PointT >

void pcl::SampleConsensusModelPlane< PointT >::projectPoints	(	const std::vector< int > &	inliers,
		const Eigen::VectorXf &	model_coefficients,
		PointCloud &	projected_points,
		bool	copy_data_fields = `true`
	)		`[virtual, inherited]`

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

Parameters:

[in]	inliers	the data inliers that we want to project on the plane model
[in]	model_coefficients	the normalized coefficients of a plane 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 245 of file sac_model_plane.hpp.

template<typename PointT , typename PointNT >

void pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::selectWithinDistance	(	const Eigen::VectorXf &	model_coefficients,
		const double	threshold,
		std::vector< int > &	inliers
	)		`[virtual]`

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

Parameters:

[in]	model_coefficients	the coefficients of a plane 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

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 45 of file sac_model_normal_plane.hpp.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::setIndices ( const boost::shared_ptr< std::vector< int > > & indices ) [inline, inherited]

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, inherited]

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, inherited]

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, typename PointNT>

void pcl::SampleConsensusModelFromNormals< PointT, PointNT >::setInputNormals ( const PointCloudNConstPtr & normals ) [inline, inherited]

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 539 of file sac_model.h.

template<typename PointT, typename PointNT>

void pcl::SampleConsensusModelFromNormals< PointT, PointNT >::setNormalDistanceWeight ( const double w ) [inline, inherited]

Set the normal angular distance weight.

Parameters:

[in] w the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. (The Euclidean distance will have weight 1-w.)

Definition at line 524 of file sac_model.h.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::setRadiusLimits	(	const double &	min_radius,
		const double &	max_radius
	)		`[inline, inherited]`

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 350 of file sac_model.h.

template<typename PointT>

void pcl::SampleConsensusModel< PointT >::setSamplesMaxDist	(	const double &	radius,
		SearchPtr	search
	)		`[inline, inherited]`

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, inherited]

Definition at line 389 of file sac_model.h.

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

/usr/src/RPM/BUILD/PCL-1.6.0-Source/sample_consensus/include/pcl/sample_consensus/sac_model_normal_plane.h
/usr/src/RPM/BUILD/PCL-1.6.0-Source/sample_consensus/include/pcl/sample_consensus/impl/sac_model_normal_plane.hpp

Public Types

Public Member Functions

Friends

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Friends And Related Function Documentation

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