org.openimaj.math.geometry.transforms

Class FundamentalModel

java.lang.Object

org.openimaj.math.geometry.transforms.FundamentalModel

All Implemented Interfaces:

Cloneable, EstimatableModel<Point2d,Point2d>, Model<Point2d,Point2d>

public class FundamentalModel
extends Object
implements EstimatableModel<Point2d,Point2d>

Implementation of a Fundamental matrix model that estimates the epipolar geometry.

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk)

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	FundamentalModel.EpipolarResidual Geometric residual that sums the distance of points from the closest epipolar line.
static class	FundamentalModel.Fundamental8PtResidual Computes the algebraic residual of the point pairs applied to the F matrix
static class	FundamentalModel.SampsonGeometricResidual ResidualCalculator based on Sampson's geometric error.

Field Summary

Fields

Modifier and Type	Field and Description
protected Jama.Matrix	fundamental
protected boolean	normalise

Constructor Summary

Constructors

Constructor and Description
FundamentalModel() Create a FundamentalModel, automatically normalising data when estimating the model
FundamentalModel(boolean norm) Create a FundamentalModel with optional automatic normalisation.

Method Summary

Modifier and Type	Method and Description
FundamentalModel	clone() Clone the model
void	denormaliseFundamental(Pair<Jama.Matrix> norms) De-normalise a fundamental estimate.
boolean	estimate(List<? extends IndependentPair<Point2d,Point2d>> data) Estimates the model from the observations in the list of data.
Jama.Matrix	getF() Get the fundamental matrix
int	numItemsToEstimate()
Point2d	predict(Point2d data) Uses the model to predict dependent data from an independent value.
void	setF(Jama.Matrix optimised) Set the Fundamental matrix

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

normalise

protected boolean normalise

fundamental

protected Jama.Matrix fundamental

Constructor Detail

FundamentalModel

public FundamentalModel()

Create a FundamentalModel, automatically normalising data when estimating the model

FundamentalModel

public FundamentalModel(boolean norm)

Create a FundamentalModel with optional automatic normalisation.

Parameters:

norm - true if the data should be automatically normalised before running the 8-point algorithm

Method Detail

estimate

public boolean estimate(List<? extends IndependentPair<Point2d,Point2d>> data)

Description copied from interface: EstimatableModel

Estimates the model from the observations in the list of data. The data must contain at least EstimatableModel.numItemsToEstimate() pairs of dependent and independent data. It may contain more, in which case the estimate method may choose to make use of this data for validation, or obtaining a better model by a least squares method for example.

Specified by:

estimate in interface EstimatableModel<Point2d,Point2d>

Parameters:

data - Data with which to estimate the model

Returns:

true if a successful estimate was made, false otherwise

See Also:

EstimatableModel.numItemsToEstimate()

denormaliseFundamental

public void denormaliseFundamental(Pair<Jama.Matrix> norms)

De-normalise a fundamental estimate. Use when estimate(List) was called with pre-normalised data.

Parameters:

norms - the normalisation transforms

predict

public Point2d predict(Point2d data)

Description copied from interface: Model

Uses the model to predict dependent data from an independent value.

Specified by:

predict in interface Model<Point2d,Point2d>

Parameters:

data - the data (independent variable)

Returns:

Dependent variable(s) predicted from the independent ones.

numItemsToEstimate

public int numItemsToEstimate()

Specified by:

numItemsToEstimate in interface EstimatableModel<Point2d,Point2d>

Returns:

The minimum number of observations required to estimate the model.

clone

public FundamentalModel clone()

Clone the model

Specified by:

clone in interface EstimatableModel<Point2d,Point2d>

Overrides:

clone in class Object

Returns:

a cloned copy

setF

public void setF(Jama.Matrix optimised)

Set the Fundamental matrix

Parameters:

optimised -

getF

public Jama.Matrix getF()

Get the fundamental matrix

Returns:

the F matrix