#include <MultiSampleConsensusProblem.hpp>

Public Types
typedef MODEL_T	model_t

Public Member Functions
	MultiSampleConsensusProblem (bool randomSeed=true)
	Contructor. More...

virtual	~MultiSampleConsensusProblem ()
	Destructor.

virtual void	getSamples (int &iterations, std::vector< std::vector< int > > &samples)
	Get samples for hypothesis generation. More...

virtual bool	isSampleGood (const std::vector< std::vector< int > > &sample) const
	Check if a set of samples for model generation is degenerate. More...

std::shared_ptr< std::vector< std::vector< int > > >	getIndices () const
	Get a pointer to the vector of multi-indices used. More...

void	drawIndexSample (std::vector< std::vector< int > > &sample)
	Sub-function for getting samples for hypothesis generation. More...

virtual std::vector< int >	getSampleSizes () const =0
	Get the number of samples needed for a hypothesis generation. Needs implementation in the child class. More...

virtual bool	computeModelCoefficients (const std::vector< std::vector< int > > &indices, model_t &outModel) const =0
	Compute a model from a set of samples. Needs implementation in the child-class. More...

virtual void	optimizeModelCoefficients (const std::vector< std::vector< int > > &inliers, const model_t &model_coefficients, model_t &optimized_coefficients)=0
	Refine the model coefficients over a given set (inliers). Needs implementation in the child-class. More...

virtual void	getSelectedDistancesToModel (const model_t &model, const std::vector< std::vector< int > > &indices, std::vector< std::vector< double > > &scores) const =0
	Compute the distances of all samples whith respect to given model coefficients. Needs implementation in the child-class. More...

virtual void	getDistancesToModel (const model_t &model_coefficients, std::vector< std::vector< double > > &distances)
	Compute the distances of all samples which respect to given model coefficients. More...

virtual void	selectWithinDistance (const model_t &model_coefficients, const double threshold, std::vector< std::vector< int > > &inliers)
	Select all the inlier samples whith respect to given model coefficients. More...

virtual int	countWithinDistance (const model_t &model_coefficients, const double threshold)
	Count all the inlier samples whith respect to given model coefficients. More...

void	setIndices (const std::vector< std::vector< int > > &indices)
	Set the indices_ variable (see member-description). More...

void	setUniformIndices (std::vector< int > N)
	Use this method if you want to use all samples. More...

int	rnd ()
	Get a random number. More...

Public Attributes
int	max_sample_checks_

std::shared_ptr< std::vector< std::vector< int > > >	indices_

std::vector< std::vector< int > >	shuffled_indices_

std::mt19937	rng_alg_
	std-based random number generator algorithm.

std::shared_ptr< std::uniform_int_distribution<> >	rng_dist_
	std-based random number generator distribution.

std::shared_ptr< std::function< int()> >	rng_gen_
	std-based random number generator.

Detailed Description

template<typename MODEL_T>
class opengv::sac::MultiSampleConsensusProblem< MODEL_T >

Basis-class for Sample-consensus problems containing the three basic functions for model-fitting. This one is using multi-indices for homogeneous sampling over groups of samples.

Member Typedef Documentation

template<typename MODEL_T>

typedef MODEL_T opengv::sac::MultiSampleConsensusProblem< MODEL_T >::model_t

The model we are trying to fit

Constructor & Destructor Documentation

template<typename MODEL_T>

opengv::sac::MultiSampleConsensusProblem< MODEL_T >::MultiSampleConsensusProblem ( bool randomSeed = true )

Contructor.

Parameters

[in] randomSeed Setting the seed of the random number generator with something unique, namely the current time.

Member Function Documentation

template<typename MODEL_T>

virtual bool opengv::sac::MultiSampleConsensusProblem< MODEL_T >::computeModelCoefficients	(	const std::vector< std::vector< int > > &	indices,
		model_t &	outModel
	)		const

pure virtual

Compute a model from a set of samples. Needs implementation in the child-class.

Parameters

[in]	indices	The multi-indices of the samples we use for the hypothesis.
[out]	outModel	The computed model.

Returns: Success?

Implemented in opengv::sac_problems::relative_pose::MultiNoncentralRelativePoseSacProblem, opengv::sac_problems::relative_pose::MultiCentralRelativePoseSacProblem, and opengv::sac_problems::absolute_pose::MultiNoncentralAbsolutePoseSacProblem.

template<typename MODEL_T>

virtual int opengv::sac::MultiSampleConsensusProblem< MODEL_T >::countWithinDistance	(	const model_t &	model_coefficients,
		const double	threshold
	)

virtual

Count all the inlier samples whith respect to given model coefficients.

Parameters

[in]	model_coefficients	The coefficients of the model hypothesis.
[in]	threshold	A maximum admissible distance threshold for determining the inliers and outliers.

Returns: The resultant number of inliers

template<typename MODEL_T>

void opengv::sac::MultiSampleConsensusProblem< MODEL_T >::drawIndexSample ( std::vector< std::vector< int > > & sample )

Sub-function for getting samples for hypothesis generation.

Parameters

[out] sample The multi-indices of the samples we attempt to use.

template<typename MODEL_T>

virtual void opengv::sac::MultiSampleConsensusProblem< MODEL_T >::getDistancesToModel	(	const model_t &	model_coefficients,
		std::vector< std::vector< double > > &	distances
	)

virtual

Compute the distances of all samples which respect to given model coefficients.

Parameters

[in]	model_coefficients	The coefficients of the model hypothesis.
[out]	distances	The resultant distances of all samples. Low distances mean a good fit.

template<typename MODEL_T>

std::shared_ptr< std::vector< std::vector<int> > > opengv::sac::MultiSampleConsensusProblem< MODEL_T >::getIndices ( ) const

Get a pointer to the vector of multi-indices used.

Returns: A pointer to the vector of multi-indices used.

template<typename MODEL_T>

virtual void opengv::sac::MultiSampleConsensusProblem< MODEL_T >::getSamples	(	int &	iterations,
		std::vector< std::vector< int > > &	samples
	)

virtual

Get samples for hypothesis generation.

Parameters

[in]	iterations	We won't try forever to get a good sample, this parameter keeps track of the iterations.
[out]	samples	The multi-indices of the samples we attempt to use.

template<typename MODEL_T>

virtual std::vector<int> opengv::sac::MultiSampleConsensusProblem< MODEL_T >::getSampleSizes ( ) const

pure virtual

Get the number of samples needed for a hypothesis generation. Needs implementation in the child class.

Returns: The number of samples in each group needed for hypothesis generation.

Implemented in opengv::sac_problems::relative_pose::MultiNoncentralRelativePoseSacProblem, opengv::sac_problems::relative_pose::MultiCentralRelativePoseSacProblem, and opengv::sac_problems::absolute_pose::MultiNoncentralAbsolutePoseSacProblem.

template<typename MODEL_T>

virtual void opengv::sac::MultiSampleConsensusProblem< MODEL_T >::getSelectedDistancesToModel	(	const model_t &	model,
		const std::vector< std::vector< int > > &	indices,
		std::vector< std::vector< double > > &	scores
	)		const

pure virtual

Compute the distances of all samples whith respect to given model coefficients. Needs implementation in the child-class.

Parameters

[in]	model	The coefficients of the model hypothesis.
[in]	indices	The multi-indices of the samples of which we compute distances.
[out]	scores	The resultant distances of the selected samples. Low distances mean a good fit.

Implemented in opengv::sac_problems::relative_pose::MultiNoncentralRelativePoseSacProblem, opengv::sac_problems::relative_pose::MultiCentralRelativePoseSacProblem, and opengv::sac_problems::absolute_pose::MultiNoncentralAbsolutePoseSacProblem.

template<typename MODEL_T>

virtual bool opengv::sac::MultiSampleConsensusProblem< MODEL_T >::isSampleGood ( const std::vector< std::vector< int > > & sample ) const

virtual

Check if a set of samples for model generation is degenerate.

Parameters

[in] sample The multi-indices of the samples we attempt to use for model instantiation.

Returns: Is this set of samples ok?

template<typename MODEL_T>

virtual void opengv::sac::MultiSampleConsensusProblem< MODEL_T >::optimizeModelCoefficients	(	const std::vector< std::vector< int > > &	inliers,
		const model_t &	model_coefficients,
		model_t &	optimized_coefficients
	)

pure virtual

Refine the model coefficients over a given set (inliers). Needs implementation in the child-class.

Parameters

[in]	inliers	The multi-indices of the inlier samples supporting the model.
[in]	model_coefficients	The initial guess for the model coefficients.
[out]	optimized_coefficients	The resultant refined coefficients.

Implemented in opengv::sac_problems::relative_pose::MultiNoncentralRelativePoseSacProblem, opengv::sac_problems::relative_pose::MultiCentralRelativePoseSacProblem, and opengv::sac_problems::absolute_pose::MultiNoncentralAbsolutePoseSacProblem.

template<typename MODEL_T>

int opengv::sac::MultiSampleConsensusProblem< MODEL_T >::rnd ( )

Get a random number.

Returns: A random number.

template<typename MODEL_T>

virtual void opengv::sac::MultiSampleConsensusProblem< MODEL_T >::selectWithinDistance	(	const model_t &	model_coefficients,
		const double	threshold,
		std::vector< std::vector< int > > &	inliers
	)

virtual

Select all the inlier samples whith respect to given model coefficients.

Parameters

[in]	model_coefficients	The coefficients of the model hypothesis.
[in]	threshold	A maximum admissible distance threshold for determining the inliers and outliers.
[out]	inliers	The resultant multi-indices of inlier samples.

template<typename MODEL_T>

void opengv::sac::MultiSampleConsensusProblem< MODEL_T >::setIndices ( const std::vector< std::vector< int > > & indices )

Set the indices_ variable (see member-description).

Parameters

[in] indices The multi-indices we want to use.

template<typename MODEL_T>

void opengv::sac::MultiSampleConsensusProblem< MODEL_T >::setUniformIndices ( std::vector< int > N )

Use this method if you want to use all samples.

Parameters

[in] N The number of samples in each group.

Member Data Documentation

template<typename MODEL_T>

std::shared_ptr< std::vector< std::vector<int> > > opengv::sac::MultiSampleConsensusProblem< MODEL_T >::indices_

The multi-indices of the samples we are using for solving the entire problem. These are not the multi-indices for generating a hypothesis, but all indices for model verification

template<typename MODEL_T>

int opengv::sac::MultiSampleConsensusProblem< MODEL_T >::max_sample_checks_

The maximum number of times we try to extract a valid set of samples

template<typename MODEL_T>

std::vector< std::vector<int> > opengv::sac::MultiSampleConsensusProblem< MODEL_T >::shuffled_indices_

A shuffled version of the multi-indices used for random sample drawing

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

include/opengv/sac/MultiSampleConsensusProblem.hpp

Public Types

Public Member Functions

Public Attributes

Detailed Description

template<typename MODEL_T> class opengv::sac::MultiSampleConsensusProblem< MODEL_T >

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<typename MODEL_T>
class opengv::sac::MultiSampleConsensusProblem< MODEL_T >