Maintain data and optimization model for orthogonal regression problems. More...

#include <rrel_orthogonal_regression.h>

Inheritance diagram for rrel_orthogonal_regression:

Public Types
enum	scale_t { NONE = 0, SINGLE = 1, MULTIPLE = 2 }
	Type of scale information this problem provides. More...
Public Member Functions
	rrel_orthogonal_regression (const vnl_matrix< double > &pts)
	Constructor from a matrix.
	rrel_orthogonal_regression (const vcl_vector< vnl_vector< double > > &pts)
	Constructor from a vector of points.
virtual	~rrel_orthogonal_regression ()
	Destructor.
unsigned int	num_samples () const
	Total number of samples.
bool	fit_from_minimal_set (const vcl_vector< int > &point_indices, vnl_vector< double > &params) const
	Generate a parameter estimate from a minimal sample set.
void	compute_residuals (const vnl_vector< double > &params, vcl_vector< double > &residuals) const
	Compute signed fit residuals relative to the parameter estimate.
bool	weighted_least_squares_fit (vnl_vector< double > &params, vnl_matrix< double > &cofact, const vcl_vector< double > *weights=0) const
	Weighted least squares parameter estimate.
void	print_points () const
	Print information as a test utility.
unsigned int	param_dof () const
	The degrees of freedom in the parameter set.
unsigned int	num_samples_to_instantiate () const
	Minimum number of samples required to uniquely instantiate a fit.
virtual unsigned int	residual_dof () const
	The degrees of freedom in the residual.
virtual unsigned int	num_unique_samples () const
	The number of "unique" samples.
virtual void	compute_weights (const vcl_vector< double > &residuals, const rrel_wls_obj *obj, double scale, vcl_vector< double > &weights) const
	Compute the weights for the given residuals.
virtual scale_t	scale_type () const
	Type of scale information the problem provides.
virtual const vcl_vector < double > &	prior_multiple_scales () const
	The prior scale vector, if available.
virtual double	prior_scale () const
	The prior scale, if available.
virtual void	set_prior_multiple_scales (const vcl_vector< double > &scales)
	Sets the scales for heteroscedastic data.
virtual void	set_prior_scale (double scale)
	Sets the scale for homoscedastic data.
virtual void	set_no_prior_scale ()
	Removes the scale information for the problem.
void	set_similarity_weights (const vcl_vector< double > &wgts)
	Set similarity weights.
const vcl_vector< double > &	similarity_weights () const
	Get similarity weights.
Protected Member Functions
void	set_param_dof (unsigned int dof)
	Set the degrees of freedom.
void	set_num_samples_for_fit (unsigned int num_samp)
	Set the number of samples needed for a unique fit.
void	set_scale_type (scale_t t)
	Set the type of prior scale.
Protected Attributes
vnl_matrix< double >	vars_

Detailed Description

Maintain data and optimization model for orthogonal regression problems.

The orthogonal regression problem is to try to solve

$X p = 0$

where $ X $ is a data matrix and $ p $ is a parameter vector, under the constraint $ ||p||=1 $ .

Each sample is a vnl_vector. Denoting the length of the vector by m, the length of parameter vector is also m. Since there is one more constraint $ ||p||=1 $ , the degrees of freedom in the parameters is actually m-1.

Definition at line 26 of file rrel_orthogonal_regression.h.

Member Enumeration Documentation

enum rrel_estimation_problem::scale_t [inherited]

Type of scale information this problem provides.

NONE: problem does not provide any scale information. SINGLE: problem provides a single prior scale (homoscedastic data). MULTIPLE: problem provides a scale for each residual (heteroscedastic data).

Enumerator:

NONE
SINGLE
MULTIPLE

Definition at line 40 of file rrel_estimation_problem.h.

Constructor & Destructor Documentation

rrel_orthogonal_regression::rrel_orthogonal_regression ( const vnl_matrix< double > & pts )

Constructor from a matrix.

Definition at line 12 of file rrel_orthogonal_regression.cxx.

rrel_orthogonal_regression::rrel_orthogonal_regression ( const vcl_vector< vnl_vector< double > > & pts )

Constructor from a vector of points.

Definition at line 25 of file rrel_orthogonal_regression.cxx.

rrel_orthogonal_regression::~rrel_orthogonal_regression ( ) [virtual]

Destructor.

Definition at line 42 of file rrel_orthogonal_regression.cxx.

Member Function Documentation

void rrel_orthogonal_regression::compute_residuals	(	const vnl_vector< double > &	params,
		vcl_vector< double > &	residuals
	)		const `[virtual]`

Compute signed fit residuals relative to the parameter estimate.

Implements rrel_estimation_problem.

Definition at line 85 of file rrel_orthogonal_regression.cxx.

void rrel_estimation_problem::compute_weights	(	const vcl_vector< double > &	residuals,
		const rrel_wls_obj *	obj,
		double	scale,
		vcl_vector< double > &	weights
	)		const `[virtual, inherited]`

Compute the weights for the given residuals.

The residuals are essentially those returned by compute_residuals(). The default behaviour is to apply obj->wgt() to each residual. Some problems, however, many need to augment the weights. Such problems should override this function (but may want to call this to compute the "basic" weights).

Definition at line 33 of file rrel_estimation_problem.cxx.

bool rrel_orthogonal_regression::fit_from_minimal_set	(	const vcl_vector< int > &	point_indices,
		vnl_vector< double > &	params
	)		const `[virtual]`

Generate a parameter estimate from a minimal sample set.

Implements rrel_estimation_problem.

Definition at line 53 of file rrel_orthogonal_regression.cxx.

unsigned int rrel_orthogonal_regression::num_samples ( ) const [virtual]

Total number of samples.

Implements rrel_estimation_problem.

Definition at line 47 of file rrel_orthogonal_regression.cxx.

unsigned int rrel_estimation_problem::num_samples_to_instantiate ( ) const [inline, inherited]

Minimum number of samples required to uniquely instantiate a fit.

dof()/num_samples_to_instantiate() gives the number of constraints per sample.

Definition at line 61 of file rrel_estimation_problem.h.

virtual unsigned int rrel_estimation_problem::num_unique_samples ( ) const [inline, virtual, inherited]

The number of "unique" samples.

In most problems, this equals num_samples. With estimation problems involving non-unique correspondences, however, the total number of possible correspondences (= num_samples()) generally much greater than the number of "unique samples" (which would be the number of points from one image).

This is used by random sampling techniques to determine the number of samples required to get a given probability of success.

Definition at line 84 of file rrel_estimation_problem.h.

unsigned int rrel_estimation_problem::param_dof ( ) const [inline, inherited]

The degrees of freedom in the parameter set.

Definition at line 57 of file rrel_estimation_problem.h.

void rrel_orthogonal_regression::print_points ( ) const

Print information as a test utility.

Definition at line 160 of file rrel_orthogonal_regression.cxx.

const vcl_vector< double > & rrel_estimation_problem::prior_multiple_scales ( ) const [virtual, inherited]

The prior scale vector, if available.

The call is valid only if scale_type() == MULTIPLE.

Definition at line 59 of file rrel_estimation_problem.cxx.

double rrel_estimation_problem::prior_scale ( ) const [virtual, inherited]

The prior scale, if available.

The call is valid only if scale_type() == SINGLE.

Definition at line 66 of file rrel_estimation_problem.cxx.

virtual unsigned int rrel_estimation_problem::residual_dof ( ) const [inline, virtual, inherited]

The degrees of freedom in the residual.

Most of the time, this would be 1 since the residual comes from a single random variable. In some problems, however, the error is the combination of more than one random variable. (For example, if the residual is a 2d Euclidean distance with possible error in both coordinates, the degrees of freedom in the error will be 2.)

Reimplemented in rrel_homography2d_est, and rrel_shift2d_est.

Definition at line 73 of file rrel_estimation_problem.h.

virtual scale_t rrel_estimation_problem::scale_type ( ) const [inline, virtual, inherited]

Type of scale information the problem provides.

Definition at line 116 of file rrel_estimation_problem.h.

void rrel_estimation_problem::set_no_prior_scale ( ) [virtual, inherited]

Removes the scale information for the problem.

Side effect: set scale_type() = NONE.

Definition at line 90 of file rrel_estimation_problem.cxx.

void rrel_estimation_problem::set_num_samples_for_fit ( unsigned int num_samp ) [inline, protected, inherited]

Set the number of samples needed for a unique fit.

Definition at line 167 of file rrel_estimation_problem.h.

void rrel_estimation_problem::set_param_dof ( unsigned int dof ) [inline, protected, inherited]

Set the degrees of freedom.

Definition at line 164 of file rrel_estimation_problem.h.

void rrel_estimation_problem::set_prior_multiple_scales ( const vcl_vector< double > & scales ) [virtual, inherited]

Sets the scales for heteroscedastic data.

Side effect: set scale_type() = MULTIPLE.

Definition at line 73 of file rrel_estimation_problem.cxx.

void rrel_estimation_problem::set_prior_scale ( double scale ) [virtual, inherited]

Sets the scale for homoscedastic data.

Side effect: set scale_type() = SINGLE.

Definition at line 83 of file rrel_estimation_problem.cxx.

void rrel_estimation_problem::set_scale_type ( scale_t t ) [inline, protected, inherited]

Set the type of prior scale.

Definition at line 170 of file rrel_estimation_problem.h.

void rrel_estimation_problem::set_similarity_weights ( const vcl_vector< double > & wgts ) [inline, inherited]

Set similarity weights.

Currently it is only used in wgted random sampling search

Definition at line 140 of file rrel_estimation_problem.h.

const vcl_vector<double>& rrel_estimation_problem::similarity_weights ( ) const [inline, inherited]

Get similarity weights.

Definition at line 144 of file rrel_estimation_problem.h.

bool rrel_orthogonal_regression::weighted_least_squares_fit	(	vnl_vector< double > &	params,
		vnl_matrix< double > &	cofact,
		const vcl_vector< double > *	weights = `0`
	)		const `[virtual]`

Weighted least squares parameter estimate.

Implements rrel_estimation_problem.

Definition at line 105 of file rrel_orthogonal_regression.cxx.

Member Data Documentation

vnl_matrix<double> rrel_orthogonal_regression::vars_ [protected]

Definition at line 59 of file rrel_orthogonal_regression.h.

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

contrib/rpl/rrel/rrel_orthogonal_regression.h
contrib/rpl/rrel/rrel_orthogonal_regression.cxx

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation