Package com.irurueta.geometry.estimators

Class MSACPointCorrespondenceAffineTransformation2DRobustEstimator

java.lang.Object

com.irurueta.geometry.estimators.AffineTransformation2DRobustEstimator

com.irurueta.geometry.estimators.PointCorrespondenceAffineTransformation2DRobustEstimator

com.irurueta.geometry.estimators.MSACPointCorrespondenceAffineTransformation2DRobustEstimator

public class MSACPointCorrespondenceAffineTransformation2DRobustEstimator
extends PointCorrespondenceAffineTransformation2DRobustEstimator

Finds the best affine 2D transformation for provided collections of matched 2D points using MSAC algorithm.

Field Summary

Fields

Modifier and Type	Field	Description
static final double	DEFAULT_THRESHOLD	Constant defining default threshold to determine whether points are inliers or not.
static final double	MIN_THRESHOLD	Minimum value that can be set as threshold.
private double	threshold	Threshold to determine whether points are inliers or not when testing possible estimation solutions.

Fields inherited from class com.irurueta.geometry.estimators.PointCorrespondenceAffineTransformation2DRobustEstimator

DEFAULT_ROBUST_METHOD, inputPoints, outputPoints

Fields inherited from class com.irurueta.geometry.estimators.AffineTransformation2DRobustEstimator

confidence, covariance, DEFAULT_CONFIDENCE, DEFAULT_KEEP_COVARIANCE, DEFAULT_MAX_ITERATIONS, DEFAULT_PROGRESS_DELTA, DEFAULT_REFINE_RESULT, inliersData, keepCovariance, locked, MAX_CONFIDENCE, MAX_PROGRESS_DELTA, maxIterations, MIN_CONFIDENCE, MIN_ITERATIONS, MIN_PROGRESS_DELTA, MINIMUM_SIZE, mListener, progressDelta, refineResult

Constructor Summary

Constructors

Constructor	Description
MSACPointCorrespondenceAffineTransformation2DRobustEstimator()	Constructor.
MSACPointCorrespondenceAffineTransformation2DRobustEstimator(AffineTransformation2DRobustEstimatorListener listener)	Constructor.
MSACPointCorrespondenceAffineTransformation2DRobustEstimator(AffineTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints)	Constructor with listener and lists of points to be used to estimate an affine 2D transformation.
MSACPointCorrespondenceAffineTransformation2DRobustEstimator(List<Point2D> inputPoints, List<Point2D> outputPoints)	Constructor with lists of points to be used to estimate an affine 2D transformation.

Method Summary

Modifier and Type	Method	Description
AffineTransformation2D	estimate()	Estimates an affine 2D transformation using a robust estimator and the best set of matched 2D point correspondences found using the robust estimator.
com.irurueta.numerical.robust.RobustEstimatorMethod	getMethod()	Returns method being used for robust estimation.
protected double	getRefinementStandardDeviation()	Gets standard deviation used for Levenberg-Marquardt fitting during refinement.
double	getThreshold()	Returns threshold to determine whether points are inliers or not when testing possible estimation solutions.
void	setThreshold(double threshold)	Sets threshold to determine whether points are inliers or not when testing possible estimation solutions.

Methods inherited from class com.irurueta.geometry.estimators.PointCorrespondenceAffineTransformation2DRobustEstimator

attemptRefine, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, getInputPoints, getOutputPoints, getQualityScores, isReady, setPoints, setQualityScores

Methods inherited from class com.irurueta.geometry.estimators.AffineTransformation2DRobustEstimator

createFromLines, createFromLines, createFromLines, createFromLines, createFromLines, createFromLines, createFromLines, createFromLines, createFromPoints, createFromPoints, createFromPoints, createFromPoints, createFromPoints, createFromPoints, createFromPoints, createFromPoints, getConfidence, getCovariance, getInliersData, getListener, getMaxIterations, getProgressDelta, isCovarianceKept, isListenerAvailable, isLocked, isResultRefined, setConfidence, setCovarianceKept, setListener, setMaxIterations, setProgressDelta, setResultRefined

Methods inherited from class java.lang.Object

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

Field Details

DEFAULT_THRESHOLD

public static final double DEFAULT_THRESHOLD

Constant defining default threshold to determine whether points are inliers or not. By default, 1.0 is considered a good value for cases where measures are done on pixels, since typically the minimum resolution is 1 pixel.

See Also:

• Constant Field Values

MIN_THRESHOLD

public static final double MIN_THRESHOLD

Minimum value that can be set as threshold. Threshold must be strictly greater than 0.0.

See Also:

• Constant Field Values

threshold

private double threshold

Threshold to determine whether points are inliers or not when testing possible estimation solutions. The threshold refers to the amount of error (i.e. distance) a possible solution has on a matched pair of points.

Constructor Details

MSACPointCorrespondenceAffineTransformation2DRobustEstimator

public MSACPointCorrespondenceAffineTransformation2DRobustEstimator()

Constructor.

MSACPointCorrespondenceAffineTransformation2DRobustEstimator

public MSACPointCorrespondenceAffineTransformation2DRobustEstimator(List<Point2D> inputPoints,
 List<Point2D> outputPoints)

Constructor with lists of points to be used to estimate an affine 2D transformation. Points in the list located at the same position are considered to be matched. Hence, both lists must have the same size, and their size must be greater or equal than MINIMUM_SIZE.

Parameters:

inputPoints - list of input points to be used to estimate an affine 2D transformation.

outputPoints - list of output points to be used to estimate an affine 2D transformation.

Throws:

IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

MSACPointCorrespondenceAffineTransformation2DRobustEstimator

public MSACPointCorrespondenceAffineTransformation2DRobustEstimator(AffineTransformation2DRobustEstimatorListener listener)

Constructor.

Parameters:

listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

MSACPointCorrespondenceAffineTransformation2DRobustEstimator

public MSACPointCorrespondenceAffineTransformation2DRobustEstimator(AffineTransformation2DRobustEstimatorListener listener,
 List<Point2D> inputPoints,
 List<Point2D> outputPoints)

Constructor with listener and lists of points to be used to estimate an affine 2D transformation. Points in the list located at the same position are considered to be matched. Hence, both lists must have the same size, and their size must be greater or equal than MINIMUM_SIZE.

Parameters:

listener - listener to be notified of events such as when estimation stars, ends or its progress significantly changes.

inputPoints - list of input points to be used to estimate an affine 2D transformation.

outputPoints - list of output points to be used to estimate an affine 2D transformation.

Throws:

IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

Method Details

getThreshold

public double getThreshold()

Returns threshold to determine whether points are inliers or not when testing possible estimation solutions. The threshold refers to the amount of error (i.e. Euclidean distance) a possible solution has on a matched pair of points.

Returns:

threshold to determine whether points are inliers or not when testing possible estimation solutions.

setThreshold

public void setThreshold(double threshold)
                  throws LockedException

Sets threshold to determine whether points are inliers or not when testing possible estimation solutions. The threshold refers to the amount of error (i.e. Euclidean distance) a possible solution has on a matched pair of points.

Parameters:

threshold - threshold to determine whether points are inliers or not.

Throws:

IllegalArgumentException - if provided values is equal or less than zero.

LockedException - if robust estimator is locked because an estimation is already in progress.

estimate

public AffineTransformation2D estimate()
                                throws LockedException,
NotReadyException,
com.irurueta.numerical.robust.RobustEstimatorException

Estimates an affine 2D transformation using a robust estimator and the best set of matched 2D point correspondences found using the robust estimator.

Specified by:

estimate in class AffineTransformation2DRobustEstimator

Returns:

an affine 2D transformation.

Throws:

LockedException - if robust estimator is locked because an estimation is already in progress.

NotReadyException - if provided input data is not enough to start the estimation.

com.irurueta.numerical.robust.RobustEstimatorException - if estimation fails for any reason (i.e. numerical instability, no solution available, etc).

getMethod

public com.irurueta.numerical.robust.RobustEstimatorMethod getMethod()

Returns method being used for robust estimation.

Specified by:

getMethod in class AffineTransformation2DRobustEstimator

Returns:

method being used for robust estimation.

getRefinementStandardDeviation

protected double getRefinementStandardDeviation()

Gets standard deviation used for Levenberg-Marquardt fitting during refinement. Returned value gives an indication of how much variance each residual has. Typically, this value is related to the threshold used on each robust estimation, since residuals of found inliers are within the range of such threshold.

Specified by:

getRefinementStandardDeviation in class AffineTransformation2DRobustEstimator

Returns:

standard deviation used for refinement.