Package com.irurueta.ar.calibration.estimators

Class PROMedSImageOfAbsoluteConicRobustEstimator

java.lang.Object

com.irurueta.ar.calibration.estimators.ImageOfAbsoluteConicRobustEstimator

com.irurueta.ar.calibration.estimators.PROMedSImageOfAbsoluteConicRobustEstimator

public class PROMedSImageOfAbsoluteConicRobustEstimator
extends ImageOfAbsoluteConicRobustEstimator

Finds the best image of absolute conic (IAC) for provided collection of homographies (2D transformations) using PROMedS algorithm.

Field Summary

Fields

Modifier and Type	Field	Description
static final double	DEFAULT_STOP_THRESHOLD	Default value to be used for stop threshold.
static final double	MIN_STOP_THRESHOLD	Minimum value that can be set as stop threshold.
private double[]	qualityScores	Quality scores corresponding to each provided homography.
private double	stopThreshold	Threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough.

Fields inherited from class com.irurueta.ar.calibration.estimators.ImageOfAbsoluteConicRobustEstimator

confidence, DEFAULT_CONFIDENCE, DEFAULT_MAX_ITERATIONS, DEFAULT_PROGRESS_DELTA, DEFAULT_ROBUST_METHOD, homographies, iacEstimator, listener, locked, MAX_CONFIDENCE, MAX_PROGRESS_DELTA, maxIterations, MIN_CONFIDENCE, MIN_ITERATIONS, MIN_PROGRESS_DELTA, progressDelta

Constructor Summary

Constructors

Constructor	Description
PROMedSImageOfAbsoluteConicRobustEstimator()	Constructor.
PROMedSImageOfAbsoluteConicRobustEstimator(double[] qualityScores)	Constructor.
PROMedSImageOfAbsoluteConicRobustEstimator(double[] qualityScores, ImageOfAbsoluteConicRobustEstimatorListener listener)	Constructor.
PROMedSImageOfAbsoluteConicRobustEstimator(ImageOfAbsoluteConicRobustEstimatorListener listener)	Constructor.
PROMedSImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies)	Constructor.
PROMedSImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies, double[] qualityScores)	Constructor.
PROMedSImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies, double[] qualityScores, ImageOfAbsoluteConicRobustEstimatorListener listener)	Constructor.
PROMedSImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies, ImageOfAbsoluteConicRobustEstimatorListener listener)	Constructor.

Method Summary

Modifier and Type	Method	Description
ImageOfAbsoluteConic	estimate()	Estimates Image of Absolute Conic (IAC)
com.irurueta.numerical.robust.RobustEstimatorMethod	getMethod()	Returns method being used for robust estimation
double[]	getQualityScores()	Returns quality scores corresponding to each provided homography.
double	getStopThreshold()	Returns threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough.
private void	internalSetQualityScores(double[] qualityScores)	Sets quality scores corresponding to each homography.
boolean	isReady()	Indicates if estimator is ready to start the IAC estimation.
void	setQualityScores(double[] qualityScores)	Sets quality scores corresponding to each provided homography.
void	setStopThreshold(double stopThreshold)	Sets threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough.

Methods inherited from class com.irurueta.ar.calibration.estimators.ImageOfAbsoluteConicRobustEstimator

create, create, create, create, create, create, getConfidence, getFocalDistanceAspectRatio, getHomographies, getListener, getMaxIterations, getMinNumberOfRequiredHomographies, getProgressDelta, isFocalDistanceAspectRatioKnown, isListenerAvailable, isLocked, isPrincipalPointAtOrigin, isZeroSkewness, residual, setConfidence, setFocalDistanceAspectRatio, setFocalDistanceAspectRatioKnown, setHomographies, setListener, setMaxIterations, setPrincipalPointAtOrigin, setProgressDelta, setZeroSkewness

Methods inherited from class java.lang.Object

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

Field Details

DEFAULT_STOP_THRESHOLD

public static final double DEFAULT_STOP_THRESHOLD

Default value to be used for stop threshold. Stop threshold can be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. Threshold is defined by equations h1'*IAC*h2 = 0 and h1'*IAC*h1 = h2'*IAC*h2 --< h1'*IAC*h1 - h2'*IAC*h2 = 0, where h1 and h2 are the 1st and 2nd columns of an homography (2D transformation). These equations are derived from the fact that rotation matrices are orthonormal.

See Also:

• Constant Field Values

MIN_STOP_THRESHOLD

public static final double MIN_STOP_THRESHOLD

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

See Also:

• Constant Field Values

stopThreshold

private double stopThreshold

Threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the PROMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.

qualityScores

private double[] qualityScores

Quality scores corresponding to each provided homography. The larger the score value the better the quality of the sample.

Constructor Details

PROMedSImageOfAbsoluteConicRobustEstimator

public PROMedSImageOfAbsoluteConicRobustEstimator()

Constructor.

PROMedSImageOfAbsoluteConicRobustEstimator

public PROMedSImageOfAbsoluteConicRobustEstimator(ImageOfAbsoluteConicRobustEstimatorListener listener)

Constructor.

Parameters:

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

PROMedSImageOfAbsoluteConicRobustEstimator

public PROMedSImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies)

Constructor.

Parameters:

homographies - list of homographies (2D transformations) used to estimate the image of absolute conic (IAC), which can be used to obtain pinhole camera intrinsic parameters.

Throws:

IllegalArgumentException - if not enough homographies are provided for default settings. Hence, at least 1 homography must be provided.

PROMedSImageOfAbsoluteConicRobustEstimator

public PROMedSImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies,
 ImageOfAbsoluteConicRobustEstimatorListener listener)

Constructor.

Parameters:

homographies - list of homographies (2D transformations) used to estimate the image of absolute conic (IAC), which can be used to obtain pinhole camera intrinsic parameters.

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

Throws:

IllegalArgumentException - if not enough homographies are provided for default settings. Hence, at least 1 homography must be provided.

PROMedSImageOfAbsoluteConicRobustEstimator

public PROMedSImageOfAbsoluteConicRobustEstimator(double[] qualityScores)

Constructor.

Parameters:

qualityScores - quality scores corresponding to each provided homography.

Throws:

IllegalArgumentException - if provided quality scores length is smaller than required number of homographies for default settings (i.e. 1 homography).

PROMedSImageOfAbsoluteConicRobustEstimator

public PROMedSImageOfAbsoluteConicRobustEstimator(double[] qualityScores,
 ImageOfAbsoluteConicRobustEstimatorListener listener)

Constructor.

Parameters:

qualityScores - quality scores corresponding to each provided homography.

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

Throws:

IllegalArgumentException - if provided quality scores length is smaller than required number of homographies for default settings (i.e. 1 homography).

PROMedSImageOfAbsoluteConicRobustEstimator

public PROMedSImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies,
 double[] qualityScores)

Constructor.

Parameters:

homographies - list of homographies (2D transformations) used to estimate the image of absolute conic (IAC), which can be used to obtain pinhole camera intrinsic parameters.

qualityScores - quality scores corresponding to each provided homography.

Throws:

IllegalArgumentException - if not enough homographies are provided for default settings (i.e. 1 homography) or quality scores and homographies don't have the same size.

PROMedSImageOfAbsoluteConicRobustEstimator

public PROMedSImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies,
 double[] qualityScores,
 ImageOfAbsoluteConicRobustEstimatorListener listener)

Constructor.

Parameters:

homographies - list of homographies (2D transformations) used to estimate the image of absolute conic (IAC), which can be used to obtain pinhole camera intrinsic parameters.

qualityScores - quality scores corresponding to each provided homography.

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

Throws:

IllegalArgumentException - if not enough homographies are provided for default settings (i.e. 1 homography) or quality scores and homographies don't have the same size.

Method Details

getStopThreshold

public double getStopThreshold()

Returns threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the PROMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.

Returns:

stop threshold to stop the algorithm prematurely when a certain accuracy has been reached.

setStopThreshold

public void setStopThreshold(double stopThreshold)
                      throws com.irurueta.geometry.estimators.LockedException

Sets threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the PROMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.

Parameters:

stopThreshold - stop threshold to stop the algorithm prematurely when a certain accuracy has been reached.

Throws:

IllegalArgumentException - if provided value is zero or negative.

com.irurueta.geometry.estimators.LockedException - if robust estimator is locked because an estimation is already in progress.

getQualityScores

public double[] getQualityScores()

Returns quality scores corresponding to each provided homography. The larger the score value the better the quality of the sampled homography

Overrides:

getQualityScores in class ImageOfAbsoluteConicRobustEstimator

Returns:

quality scores corresponding to each homography.

setQualityScores

public void setQualityScores(double[] qualityScores)
                      throws com.irurueta.geometry.estimators.LockedException

Sets quality scores corresponding to each provided homography. The larger the score value the better the quality of the sampled homography.

Overrides:

setQualityScores in class ImageOfAbsoluteConicRobustEstimator

Parameters:

qualityScores - quality scores corresponding to each homography.

Throws:

com.irurueta.geometry.estimators.LockedException - if robust estimator is locked because an estimation is already in progress.

IllegalArgumentException - if provided quality scores length is smaller than minimum required number of homographies (i.e. 1 homography).

isReady

public boolean isReady()

Indicates if estimator is ready to start the IAC estimation. This is true when input data (i.e. homographies) is provided and list contains at least the minimum number of required homographies, and also quality scores are provided.

Overrides:

isReady in class ImageOfAbsoluteConicRobustEstimator

Returns:

true if estimator is ready, false otherwise.

estimate

public ImageOfAbsoluteConic estimate()
                              throws com.irurueta.geometry.estimators.LockedException,
com.irurueta.geometry.estimators.NotReadyException,
com.irurueta.numerical.robust.RobustEstimatorException

Estimates Image of Absolute Conic (IAC)

Specified by:

estimate in class ImageOfAbsoluteConicRobustEstimator

Returns:

estimated IAC

Throws:

com.irurueta.geometry.estimators.LockedException - if robust estimator is locked because an estimation is already in progress

com.irurueta.geometry.estimators.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 ImageOfAbsoluteConicRobustEstimator

Returns:

method being used for robust estimation

internalSetQualityScores

private void internalSetQualityScores(double[] qualityScores)

Sets quality scores corresponding to each homography. This method is used internally and does not check whether instance is locked or not.

Parameters:

qualityScores - quality scores to be set.

Throws:

IllegalArgumentException - if provided quality scores length is smaller than the minimum number of required homographies for current settings.