Package com.irurueta.geometry.estimators
Class MSACPointCorrespondenceAffineTransformation3DRobustEstimator
java.lang.Object
com.irurueta.geometry.estimators.AffineTransformation3DRobustEstimator
com.irurueta.geometry.estimators.PointCorrespondenceAffineTransformation3DRobustEstimator
com.irurueta.geometry.estimators.MSACPointCorrespondenceAffineTransformation3DRobustEstimator
public class MSACPointCorrespondenceAffineTransformation3DRobustEstimator
extends PointCorrespondenceAffineTransformation3DRobustEstimator
Finds the best affine 3D transformation for provided collections of matched
3D points using MSAC algorithm.
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Field Summary
FieldsModifier and TypeFieldDescriptionstatic final doubleConstant defining default threshold to determine whether points are inliers or not.static final doubleMinimum value that can be set as threshold.private doubleThreshold to determine whether points are inliers or not when testing possible estimation solutions.Fields inherited from class com.irurueta.geometry.estimators.PointCorrespondenceAffineTransformation3DRobustEstimator
DEFAULT_ROBUST_METHOD, inputPoints, outputPointsFields inherited from class com.irurueta.geometry.estimators.AffineTransformation3DRobustEstimator
confidence, covariance, DEFAULT_CONFIDENCE, DEFAULT_KEEP_COVARIANCE, DEFAULT_MAX_ITERATIONS, DEFAULT_PROGRESS_DELTA, DEFAULT_REFINE_RESULT, inliersData, keepCovariance, listener, locked, MAX_CONFIDENCE, MAX_PROGRESS_DELTA, maxIterations, MIN_CONFIDENCE, MIN_ITERATIONS, MIN_PROGRESS_DELTA, MINIMUM_SIZE, progressDelta, refineResult -
Constructor Summary
ConstructorsConstructorDescriptionConstructor.MSACPointCorrespondenceAffineTransformation3DRobustEstimator(AffineTransformation3DRobustEstimatorListener listener) Constructor.MSACPointCorrespondenceAffineTransformation3DRobustEstimator(AffineTransformation3DRobustEstimatorListener listener, List<Point3D> inputPoints, List<Point3D> outputPoints) Constructor with listener and lists of points to be used to estimate an affine 3D transformation.MSACPointCorrespondenceAffineTransformation3DRobustEstimator(List<Point3D> inputPoints, List<Point3D> outputPoints) Constructor with lists of points to be used to estimate an affine 3D transformation. -
Method Summary
Modifier and TypeMethodDescriptionestimate()Estimates an affine 3D transformation using a robust estimator and the best set of matched 3D point correspondences found using the robust estimator.com.irurueta.numerical.robust.RobustEstimatorMethodReturns method being used for robust estimation.protected doubleGets standard deviation used for Levenberg-Marquardt fitting during refinement.doubleReturns threshold to determine whether points are inliers or not when testing possible estimation solutions.voidsetThreshold(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.PointCorrespondenceAffineTransformation3DRobustEstimator
attemptRefine, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, getInputPoints, getOutputPoints, getQualityScores, isReady, setPoints, setQualityScoresMethods inherited from class com.irurueta.geometry.estimators.AffineTransformation3DRobustEstimator
createFromPlanes, createFromPlanes, createFromPlanes, createFromPlanes, createFromPlanes, createFromPlanes, createFromPlanes, createFromPlanes, createFromPoints, createFromPoints, createFromPoints, createFromPoints, createFromPoints, createFromPoints, createFromPoints, createFromPoints, getConfidence, getCovariance, getInliersData, getListener, getMaxIterations, getProgressDelta, isCovarianceKept, isListenerAvailable, isLocked, isResultRefined, setConfidence, setCovarianceKept, setListener, setMaxIterations, setProgressDelta, setResultRefined
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Field Details
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DEFAULT_THRESHOLD
public static final double DEFAULT_THRESHOLDConstant 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 voxels, since typically the minimum resolution is 1 voxel (the equivalent of a pixel in 3D).- See Also:
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MIN_THRESHOLD
public static final double MIN_THRESHOLDMinimum value that can be set as threshold. Threshold must be strictly greater than 0.0.- See Also:
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threshold
private double thresholdThreshold 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.
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Constructor Details
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MSACPointCorrespondenceAffineTransformation3DRobustEstimator
public MSACPointCorrespondenceAffineTransformation3DRobustEstimator()Constructor. -
MSACPointCorrespondenceAffineTransformation3DRobustEstimator
public MSACPointCorrespondenceAffineTransformation3DRobustEstimator(List<Point3D> inputPoints, List<Point3D> outputPoints) Constructor with lists of points to be used to estimate an affine 3D 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 3D transformation.outputPoints- list of output points to be used to estimate an affine 3D transformation.- Throws:
IllegalArgumentException- if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.
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MSACPointCorrespondenceAffineTransformation3DRobustEstimator
public MSACPointCorrespondenceAffineTransformation3DRobustEstimator(AffineTransformation3DRobustEstimatorListener listener) Constructor.- Parameters:
listener- listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
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MSACPointCorrespondenceAffineTransformation3DRobustEstimator
public MSACPointCorrespondenceAffineTransformation3DRobustEstimator(AffineTransformation3DRobustEstimatorListener listener, List<Point3D> inputPoints, List<Point3D> outputPoints) Constructor with listener and lists of points to be used to estimate an affine 3D 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 3D transformation.outputPoints- list of output points to be used to estimate an affine 3D transformation.- Throws:
IllegalArgumentException- if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.
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Method Details
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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.
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setThreshold
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.
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estimate
public AffineTransformation3D estimate() throws LockedException, NotReadyException, com.irurueta.numerical.robust.RobustEstimatorExceptionEstimates an affine 3D transformation using a robust estimator and the best set of matched 3D point correspondences found using the robust estimator.- Specified by:
estimatein classAffineTransformation3DRobustEstimator- Returns:
- an affine 3D 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).
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getMethod
public com.irurueta.numerical.robust.RobustEstimatorMethod getMethod()Returns method being used for robust estimation.- Specified by:
getMethodin classAffineTransformation3DRobustEstimator- Returns:
- method being used for robust estimation.
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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:
getRefinementStandardDeviationin classAffineTransformation3DRobustEstimator- Returns:
- standard deviation used for refinement.
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