lti::fMatrixEstimator Class Reference

A class for estimating the fundamental matrix with a least squares approach. More...

#include <ltiFMatrixEstimator.h>

Inheritance diagram for lti::fMatrixEstimator:

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Collaboration diagram for lti::fMatrixEstimator:

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List of all members.

Classes
class	parameters
	The parameters for the class fMatrixEstimator. More...
Public Member Functions
	fMatrixEstimator ()
	fMatrixEstimator (const parameters &par)
	fMatrixEstimator (const fMatrixEstimator &other)
virtual	~fMatrixEstimator ()
virtual const char *	getTypeName () const
virtual bool	apply (const matrix< ipoint > &src, fvector &dest) const
virtual bool	apply (const matrix< ipoint > &src, fvector &dest, fvector &error) const
virtual bool	apply (const matrix< ipoint > &src, fvector &dest, const ivector &indices, int numCorrespondences) const
virtual bool	apply (const matrix< ipoint > &src, fvector &dest, fvector &error, const ivector &indices, int numCorrespondences) const
virtual bool	apply (const matrix< fpoint > &src, fvector &dest) const
virtual bool	apply (const matrix< fpoint > &src, fvector &dest, fvector &error) const
virtual bool	apply (const matrix< fpoint > &src, fvector &dest, const ivector &indices, int numCorrespondences) const
virtual bool	apply (const matrix< fpoint > &src, fvector &dest, fvector &error, const ivector &indices, int numCorrespondences) const
virtual bool	apply (const matrix< dpoint > &src, dvector &dest) const
virtual bool	apply (const matrix< dpoint > &src, dvector &dest, dvector &error) const
virtual bool	apply (const matrix< dpoint > &src, dvector &dest, const ivector &indices, int numCorrespondences) const
virtual bool	apply (const matrix< dpoint > &src, dvector &dest, dvector &error, const ivector &indices, int numCorrespondences) const
virtual bool	computeResidual (const matrix< fpoint > &src, const fvector &transform, fvector &dest) const
virtual bool	computeResidual (const matrix< dpoint > &src, const dvector &transform, dvector &dest) const
virtual int	minNumberCorrespondences () const
virtual int	minCorrespondenceDimension () const
virtual int	maxCorrespondenceDimension () const
bool	denormalize (fvector &srcdest, const vector< fpoint > &scale, const vector< fpoint > &shift) const
bool	denormalize (dvector &srcdest, const vector< dpoint > &scale, const vector< dpoint > &shift) const
bool	convert (const fvector &src, fmatrix &dest) const
bool	convert (const dvector &src, dmatrix &dest) const
fMatrixEstimator &	copy (const fMatrixEstimator &other)
fMatrixEstimator &	operator= (const fMatrixEstimator &other)
virtual functor *	clone () const
const parameters &	getParameters () const

---

Detailed Description

A class for estimating the fundamental matrix with a least squares approach.

---

Constructor & Destructor Documentation

lti::fMatrixEstimator::fMatrixEstimator

(

)

Default constructor.

lti::fMatrixEstimator::fMatrixEstimator

(

const parameters &

par

)

Construct a functor using the given parameters.

lti::fMatrixEstimator::fMatrixEstimator

(

const fMatrixEstimator &

other

)

Copy constructor.

Parameters:

other

the object to be copied

virtual lti::fMatrixEstimator::~fMatrixEstimator

(

)

[virtual]

Destructor.

---

Member Function Documentation

virtual bool lti::fMatrixEstimator::apply	(	const matrix< dpoint > &	src,
		dvector &	dest,
		dvector &	error,
		const ivector &	indices,
		int	numCorrespondences
	)			const [virtual]

Estimates a transform from the supplied point sets, whereby only the points specified in the index vector are considered.

Usually this method calls the apply without the residual first, and then computes the residual.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<dpoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	dvector the estimated transform.
	error	dvector containing the deviation of each point from the estimated transform. Usually this is the residual or elementwise squared residual.
	indices	ivector with the indices of the relevant points.
	numCorrespondences	the first numCorrespondences indices are considered.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< dpoint > &	src,
		dvector &	dest,
		const ivector &	indices,
		int	numCorrespondences
	)			const [virtual]

Estimates a transform from the supplied point sets, whereby only the points specified in the index vector are considered.

This method is used by robost estimators using a monte carlo approach.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<dpoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	dvector the estimated transform.
	indices	ivector with the indices of the relevant points.
	numCorrespondences	the first numCorrespondences indices are considered.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< dpoint > &	src,
		dvector &	dest,
		dvector &	error
	)			const [virtual]

Estimates a transform from the supplied point sets, where all points are considered.

Usually this method calls the apply without the residual first, and then computes the residual.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<dpoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	dvector the estimated transform.
	error	dvector containing the deviation of each point from the estimated transform. Usually this is the residual or elementwise squared residual.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< dpoint > &	src,
		dvector &	dest
	)			const [virtual]

Estimates a transform from the supplied point sets, where all points are considered.

Please implement efficient code using iterators here. Not all robust estimators use a random sampling approach. Some estimators consider all input points and weight them according to their deviation from the transform computed at the prior iteration.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<dpoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	dvector the estimated transform.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< fpoint > &	src,
		fvector &	dest,
		fvector &	error,
		const ivector &	indices,
		int	numCorrespondences
	)			const [virtual]

Estimates a transform from the supplied point sets, whereby only the points specified in the index vector are considered.

Usually this method calls the apply without the residual first, and then computes the residual.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<fpoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	fvector the estimated transform.
	error	fvector containing the deviation of each point from the estimated transform. Usually this is the residual or elementwise squared residual.
	indices	ivector with the indices of the relevant points.
	numCorrespondences	the first numCorrespondences indices are considered.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< fpoint > &	src,
		fvector &	dest,
		const ivector &	indices,
		int	numCorrespondences
	)			const [virtual]

Estimates a transform from the supplied point sets, whereby only the points specified in the index vector are considered.

This method is used by robost estimators using a monte carlo approach.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<fpoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	fvector the estimated transform.
	indices	ivector with the indices of the relevant points.
	numCorrespondences	the first numCorrespondences indices are considered.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< fpoint > &	src,
		fvector &	dest,
		fvector &	error
	)			const [virtual]

Estimates a transform from the supplied point sets, where all points are considered.

Usually this method calls the apply without the residual first, and then computes the residual.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<fpoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	fvector the estimated transform.
	error	fvector containing the deviation of each point from the estimated transform. Usually this is the residual or elementwise squared residual.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< fpoint > &	src,
		fvector &	dest
	)			const [virtual]

Estimates a transform from the supplied point sets, where all points are considered.

Please implement efficient code using iterators here. Not all robust estimators use a random sampling approach. Some estimators consider all input points and weight them according to their deviation from the transform computed at the prior iteration.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<fpoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	fvector the estimated transform.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< ipoint > &	src,
		fvector &	dest,
		fvector &	error,
		const ivector &	indices,
		int	numCorrespondences
	)			const [virtual]

Estimates a transform from the supplied point sets, whereby only the points specified in the index vector are considered.

Usually this method calls the apply without the residual first, and then computes the residual.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<ipoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	fvector the estimated transform.
	error	fvector containing the deviation of each point from the estimated transform. Usually this is the residual or elementwise squared residual.
	indices	ivector with the indices of the relevant points.
	numCorrespondences	the first numCorrespondences indices are considered.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< ipoint > &	src,
		fvector &	dest,
		const ivector &	indices,
		int	numCorrespondences
	)			const [virtual]

Estimates a transform from the supplied point sets, whereby only the points specified in the index vector are considered.

This method is used by robost estimators using a monte carlo approach.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<ipoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	fvector the estimated transform.
	indices	ivector with the indices of the relevant points.
	numCorrespondences	the first numCorrespondences indices are considered.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< ipoint > &	src,
		fvector &	dest,
		fvector &	error
	)			const [virtual]

Estimates a transform from the supplied point sets, where all points are considered.

Usually this method calls the apply without the residual first, and then computes the residual.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<ipoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	fvector the estimated transform.
	error	fvector containing the deviation of each point from the estimated transform. Usually this is the residual or elementwise squared residual.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::apply	(	const matrix< ipoint > &	src,
		fvector &	dest
	)			const [virtual]

Estimates a transform from the supplied point sets, where all points are considered.

Please implement efficient code using iterators here. Not all robust estimators use a random sampling approach. Some estimators consider all input points and weight them according to their deviation from the transform computed at the prior iteration.

All points of one point set give a matrix row, whereas all elements of a specifec correspondence stand in a matrix column.

Parameters:

	src	matrix<ipoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	dest	fvector the estimated transform.

Returns:

true if apply successful or false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual functor* lti::fMatrixEstimator::clone

(

)

const [virtual]

Returns a pointer to a clone of this functor.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::computeResidual	(	const matrix< dpoint > &	src,
		const dvector &	transform,
		dvector &	dest
	)			const [virtual]

Compute the residual for the given correspondences and transformation vector.

Parameters:

	src	matrix<dpoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	transform	dvector with the transformation
	dest	dvector with the residual

Returns:

true on success and false otherwise.

Implements lti::fMatrixEstimatorBase.

virtual bool lti::fMatrixEstimator::computeResidual	(	const matrix< fpoint > &	src,
		const fvector &	transform,
		fvector &	dest
	)			const [virtual]

Compute the residual for the given correspondences and transformation vector.

Parameters:

	src	matrix<fpoint> with the point sets. All points of the same image stand in a row. The correspondences in another image stand in the according columns.
	transform	fvector with the transformation
	dest	fvector with the residual

Returns:

true on success and false otherwise.

Implements lti::fMatrixEstimatorBase.

bool lti::fMatrixEstimator::convert	(	const dvector &	src,
		dmatrix &	dest
	)			const

Converts the estimated vector into a 3x3 matrix.

Parameters:

	src	dvector the estimated transform.
	dest	dmatrix the estimated transform as a matrix.

Returns:

true if successful or false otherwise.

bool lti::fMatrixEstimator::convert	(	const fvector &	src,
		fmatrix &	dest
	)			const

Converts the estimated vector into a 3x3 matrix.

Parameters:

	src	fvector the estimated transform.
	dest	fmatrix the estimated transform as a matrix.

Returns:

true if successful or false otherwise.

fMatrixEstimator& lti::fMatrixEstimator::copy

(

const fMatrixEstimator &

other

)

Copy data of "other" functor.

Parameters:

other

the functor to be copied

Returns:

a reference to this functor object

Reimplemented from lti::fMatrixEstimatorBase.

bool lti::fMatrixEstimator::denormalize	(	dvector &	srcdest,
		const vector< dpoint > &	scale,
		const vector< dpoint > &	shift
	)			const [virtual]

A transform estimated on normalized data usually differs from the transform of the original data.

Considering the normalization performed this methods computes the transform which applies to the original data.

Parameters:

	srcdest	the normalized transform. The result will be left here too.
	scale	a vector containing the scale applied to each point set.
	shift	a vector containing the shift of each scaled point set.

Implements lti::fMatrixEstimatorBase.

bool lti::fMatrixEstimator::denormalize	(	fvector &	srcdest,
		const vector< fpoint > &	scale,
		const vector< fpoint > &	shift
	)			const [virtual]

A transform estimated on normalized data usually differs from the transform of the original data.

Considering the normalization performed this methods computes the transform which applies to the original data.

Parameters:

	srcdest	the normalized transform. The result will be left here too.
	scale	a vector containing the scale applied to each point set.
	shift	a vector containing the shift of each scaled point set.

Implements lti::fMatrixEstimatorBase.

const parameters& lti::fMatrixEstimator::getParameters

(

)

const

Returns used parameters.

Reimplemented from lti::fMatrixEstimatorBase.

virtual const char* lti::fMatrixEstimator::getTypeName

(

)

const [virtual]

Returns the name of this type ("fMatrixEstimator").

Reimplemented from lti::fMatrixEstimatorBase.

virtual int lti::fMatrixEstimator::maxCorrespondenceDimension

(

)

const [virtual]

Returns the maximum dimension of a correspondence, e.g.

the maximum dimension of a correspondence pair is 2, whereas transformEstimator running on n-tuples may allow an infinite number. Each derived transform estimator only works on correspondences of priori defined dimensions.

Implements lti::fMatrixEstimatorBase.

virtual int lti::fMatrixEstimator::minCorrespondenceDimension

(

)

const [virtual]

Returns the mininum dimension of a correspondence, e.g.

the minimum dimension of a correspondence pair is 2. Each derived transform estimator only works on correspondences of priori defined dimensions.

Implements lti::fMatrixEstimatorBase.

virtual int lti::fMatrixEstimator::minNumberCorrespondences

(

)

const [virtual]

Returns the minimum number of correspondences required to estimate the transform.

Implements lti::fMatrixEstimatorBase.

fMatrixEstimator& lti::fMatrixEstimator::operator=

(

const fMatrixEstimator &

other

)

Alias for copy member.

Parameters:

other

the functor to be copied

Returns:

a reference to this functor object

Reimplemented from lti::fMatrixEstimatorBase.

---

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

• ltiFMatrixEstimator.h