sample_consensus::SACModelSphere Class Reference

A Sample Consensus Model class for sphere segmentation. More...

#include <sac_model_sphere.h>

Inheritance diagram for sample_consensus::SACModelSphere:

Public Member Functions
virtual bool	computeModelCoefficients (const std::vector< int > &samples)
	Check whether the given index samples can form a valid sphere model, compute the model coefficients from these samples and store them internally in model_coefficients_. The sphere coefficients are: x, y, z, R.
virtual bool	doSamplesVerifyModel (const std::set< int > &indices, double threshold)
	Verify whether a subset of indices verifies the internal sphere model coefficients.
virtual void	getDistancesToModel (const std::vector< double > &model_coefficients, std::vector< double > &distances)
	Compute all distances from the cloud data to a given sphere model.
virtual int	getModelType ()
	Return an unique id for this model (SACMODEL_SPHERE).
virtual void	getSamples (int &iterations, std::vector< int > &samples)
	Get 4 random points (3 non-collinear) as data samples and return them as point indices.
virtual void	projectPoints (const std::vector< int > &inliers, const std::vector< double > &model_coefficients, sensor_msgs::PointCloud &projected_points)
	Create a new point cloud with inliers projected onto the sphere model.
virtual void	projectPointsInPlace (const std::vector< int > &inliers, const std::vector< double > &model_coefficients)
	Project inliers (in place) onto the given sphere model.
virtual void	refitModel (const std::vector< int > &inliers, std::vector< double > &refit_coefficients)
	Recompute the sphere coefficients using the given inlier set and return them to the user.
	SACModelSphere ()
	Constructor for base SACModelSphere.
virtual void	selectWithinDistance (const std::vector< double > &model_coefficients, double threshold, std::vector< int > &inliers)
	Select all the points which respect the given model coefficients as inliers.
bool	testModelCoefficients (const std::vector< double > &model_coefficients)
	Test whether the given model coefficients are valid given the input point cloud data.
virtual	~SACModelSphere ()
	Destructor for base SACModelSphere.
Static Public Member Functions
static int	functionToOptimize (void p, int m, int n, const double x, double *fvec, int iflag)
	Cost function to be minimized.
Private Attributes
const std::vector< int > *	tmp_inliers_
	temporary pointer to a list of given indices for refitModel ()

Detailed Description

A Sample Consensus Model class for sphere segmentation.

Definition at line 46 of file sac_model_sphere.h.

Constructor & Destructor Documentation

sample_consensus::SACModelSphere::SACModelSphere ( ) [inline]

Constructor for base SACModelSphere.

Definition at line 51 of file sac_model_sphere.h.

virtual sample_consensus::SACModelSphere::~SACModelSphere ( ) [inline, virtual]

Destructor for base SACModelSphere.

Definition at line 55 of file sac_model_sphere.h.

Member Function Documentation

bool sample_consensus::SACModelSphere::computeModelCoefficients ( const std::vector< int > & samples ) [virtual]

Check whether the given index samples can form a valid sphere model, compute the model coefficients from these samples and store them internally in model_coefficients_. The sphere coefficients are: x, y, z, R.

Parameters:

samples

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

Implements sample_consensus::SACModel.

Definition at line 214 of file sac_model_sphere.cpp.

bool sample_consensus::SACModelSphere::doSamplesVerifyModel	(	const std::set< int > &	indices,
		double	threshold
	)			`[virtual]`

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

Parameters:

	indices	the data indices that need to be tested against the sphere model
	threshold	a maximum admissible distance threshold for determining the inliers from the outliers

Implements sample_consensus::SACModel.

Definition at line 362 of file sac_model_sphere.cpp.

int sample_consensus::SACModelSphere::functionToOptimize	(	void *	p,
		int	m,
		int	n,
		const double *	x,
		double *	fvec,
		int	iflag
	)			`[static]`

Cost function to be minimized.

Parameters:

	p	a pointer to our data structure array
	m	the number of functions
	n	the number of variables
	x	a pointer to the variables array
	fvec	a pointer to the resultant functions evaluations
	iflag	set to -1 inside the function to terminate execution

Definition at line 339 of file sac_model_sphere.cpp.

void sample_consensus::SACModelSphere::getDistancesToModel	(	const std::vector< double > &	model_coefficients,
		std::vector< double > &	distances
	)			`[virtual]`

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

Parameters:

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

Implements sample_consensus::SACModel.

Definition at line 160 of file sac_model_sphere.cpp.

virtual int sample_consensus::SACModelSphere::getModelType ( ) [inline, virtual]

Return an unique id for this model (SACMODEL_SPHERE).

Implements sample_consensus::SACModel.

Definition at line 81 of file sac_model_sphere.h.

void sample_consensus::SACModelSphere::getSamples	(	int &	iterations,
		std::vector< int > &	samples
	)			`[virtual]`

Get 4 random points (3 non-collinear) as data samples and return them as point indices.

Parameters:

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

Note:: assumes unique points!; Two different points could be enough in theory, to infere some sort of a center and a radius, but in practice, we might end up with a lot of points which are just 'close' to one another. Therefore we have two options: a) use normal information (good but I wouldn't rely on it in extremely noisy point clouds, no matter what) b) get two more points and uniquely identify a sphere in space (3 unique points define a circle)

Implements sample_consensus::SACModel.

Definition at line 47 of file sac_model_sphere.cpp.

void sample_consensus::SACModelSphere::projectPoints	(	const std::vector< int > &	inliers,
		const std::vector< double > &	model_coefficients,
		sensor_msgs::PointCloud &	projected_points
	)			`[virtual]`

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

Parameters:

	inliers	the data inliers that we want to project on the sphere model
	model_coefficients	the coefficients of a sphere model
	projected_points	the resultant projected points

Todo:: implement this.

Implements sample_consensus::SACModel.

Definition at line 189 of file sac_model_sphere.cpp.

void sample_consensus::SACModelSphere::projectPointsInPlace	(	const std::vector< int > &	inliers,
		const std::vector< double > &	model_coefficients
	)			`[virtual]`

Project inliers (in place) onto the given sphere model.

Parameters:

	inliers	the data inliers that we want to project on the sphere model
	model_coefficients	the coefficients of a sphere model

Todo:: implement this.

Implements sample_consensus::SACModel.

Definition at line 203 of file sac_model_sphere.cpp.

void sample_consensus::SACModelSphere::refitModel	(	const std::vector< int > &	inliers,
		std::vector< double > &	refit_coefficients
	)			`[virtual]`

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

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

Parameters:

	inliers	the data inliers found as supporting the model
	refit_coefficients	the resultant recomputed coefficients after non-linear optimization

Implements sample_consensus::SACModel.

Definition at line 279 of file sac_model_sphere.cpp.

void sample_consensus::SACModelSphere::selectWithinDistance	(	const std::vector< double > &	model_coefficients,
		double	threshold,
		std::vector< int > &	inliers
	)			`[virtual]`

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

Parameters:

	model_coefficients	the coefficients of a sphere 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

Note:: : To get the refined inliers of a model, use: ANNpoint refined_coeff = refitModel (...); selectWithinDistance (refined_coeff, threshold);

Implements sample_consensus::SACModel.

Definition at line 124 of file sac_model_sphere.cpp.

bool sample_consensus::SACModelSphere::testModelCoefficients ( const std::vector< double > & model_coefficients ) [inline, virtual]

Test whether the given model coefficients are valid given the input point cloud data.

Parameters:

model_coefficients

the model coefficients that need to be tested

Todo:: implement this

Implements sample_consensus::SACModel.

Definition at line 64 of file sac_model_sphere.h.

Member Data Documentation

const std::vector<int>* sample_consensus::SACModelSphere::tmp_inliers_ [private]

temporary pointer to a list of given indices for refitModel ()

Definition at line 85 of file sac_model_sphere.h.

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

sample_consensus::SACModelSphere Class Reference

Public Member Functions

Static Public Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation