org.openimaj.math.geometry.transforms.estimation

Class RobustAffineTransformEstimator

java.lang.Object

org.openimaj.math.geometry.transforms.estimation.RobustAffineTransformEstimator

All Implemented Interfaces:

ModelFitting<Point2d,Point2d,AffineTransformModel>, RobustModelFitting<Point2d,Point2d,AffineTransformModel>

public class RobustAffineTransformEstimator
extends Object
implements RobustModelFitting<Point2d,Point2d,AffineTransformModel>

Helper class to simplify robust estimation of 2D affine transforms without having to deal with the nuts and bolts of the underlying robust model fitters, etc. The overall robust estimation process uses the normalised DLT algorithm (see TransformUtilities.affineMatrix(List)) coupled with either RANSAC or LMedS with a BucketingSampler2d sampling strategy for selecting subsets.

Non-linear optimisation is unncessary as the algebraic and geometric distances are equal in the affine case.

Author:

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

Constructor Summary

Constructors

Constructor and Description
RobustAffineTransformEstimator(double outlierProportion) Construct using the LMedS algorithm with the given expected outlier percentage
RobustAffineTransformEstimator(double threshold, int nIterations, RANSAC.StoppingCondition stoppingCondition) Construct using the RANSAC algorithm with the given options.
RobustAffineTransformEstimator(double threshold, int nIterations, RANSAC.StoppingCondition stoppingCondition, Predicate<AffineTransformModel> modelCheck) Construct using the RANSAC algorithm with the given options.
RobustAffineTransformEstimator(double outlierProportion, Predicate<AffineTransformModel> modelCheck) Construct using the LMedS algorithm with the given expected outlier percentage

Method Summary

Modifier and Type	Method and Description
boolean	fitData(List<? extends IndependentPair<Point2d,Point2d>> data) Attempt to fit the given data to the model.
List<? extends IndependentPair<Point2d,Point2d>>	getInliers()
AffineTransformModel	getModel()
List<? extends IndependentPair<Point2d,Point2d>>	getOutliers()
int	numItemsToEstimate()

Methods inherited from class java.lang.Object

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

Constructor Detail

RobustAffineTransformEstimator

public RobustAffineTransformEstimator(double outlierProportion)

Construct using the LMedS algorithm with the given expected outlier percentage

Parameters:

outlierProportion - expected proportion of outliers (between 0 and 1)

RobustAffineTransformEstimator

public RobustAffineTransformEstimator(double threshold,
                                      int nIterations,
                                      RANSAC.StoppingCondition stoppingCondition)

Construct using the RANSAC algorithm with the given options.

Parameters:

threshold - the threshold on the AlgebraicResidual2d at which to consider a point as an inlier

nIterations - the maximum number of iterations

stoppingCondition - the RANSAC.StoppingCondition for RANSAC

RobustAffineTransformEstimator

public RobustAffineTransformEstimator(double outlierProportion,
                                      Predicate<AffineTransformModel> modelCheck)

Construct using the LMedS algorithm with the given expected outlier percentage

Parameters:

outlierProportion - expected proportion of outliers (between 0 and 1)

modelCheck - the predicate to test whether an estimated model is sane

RobustAffineTransformEstimator

public RobustAffineTransformEstimator(double threshold,
                                      int nIterations,
                                      RANSAC.StoppingCondition stoppingCondition,
                                      Predicate<AffineTransformModel> modelCheck)

Construct using the RANSAC algorithm with the given options.

Parameters:

threshold - the threshold on the AlgebraicResidual2d at which to consider a point as an inlier

nIterations - the maximum number of iterations

stoppingCondition - the RANSAC.StoppingCondition for RANSAC

modelCheck - the predicate to test whether an estimated model is sane

Method Detail

fitData

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

Description copied from interface: ModelFitting

Attempt to fit the given data to the model.

Specified by:

fitData in interface ModelFitting<Point2d,Point2d,AffineTransformModel>

Parameters:

data - Data to be fitted

Returns:

true on success, false otherwise

numItemsToEstimate

public int numItemsToEstimate()

Specified by:

numItemsToEstimate in interface ModelFitting<Point2d,Point2d,AffineTransformModel>

Returns:

The minimum number of observations required to estimate the model.

getModel

public AffineTransformModel getModel()

Specified by:

getModel in interface ModelFitting<Point2d,Point2d,AffineTransformModel>

Returns:

the trained model object

getInliers

public List<? extends IndependentPair<Point2d,Point2d>> getInliers()

Specified by:

getInliers in interface RobustModelFitting<Point2d,Point2d,AffineTransformModel>

Returns:

list of the inliers in the original data

getOutliers

public List<? extends IndependentPair<Point2d,Point2d>> getOutliers()

Specified by:

getOutliers in interface RobustModelFitting<Point2d,Point2d,AffineTransformModel>

Returns:

list of the outliers in the original data