PROMedSFundamentalMatrixRobustEstimator.java
/*
* Copyright (C) 2015 Alberto Irurueta Carro (alberto@irurueta.com)
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.irurueta.ar.epipolar.estimators;
import com.irurueta.ar.epipolar.FundamentalMatrix;
import com.irurueta.geometry.Point2D;
import com.irurueta.geometry.estimators.LockedException;
import com.irurueta.geometry.estimators.NotReadyException;
import com.irurueta.numerical.robust.PROMedSRobustEstimator;
import com.irurueta.numerical.robust.PROMedSRobustEstimatorListener;
import com.irurueta.numerical.robust.RobustEstimator;
import com.irurueta.numerical.robust.RobustEstimatorException;
import com.irurueta.numerical.robust.RobustEstimatorMethod;
import java.util.ArrayList;
import java.util.List;
/**
* Finds the best fundamental matrix for provided collections of matched 2D
* points using PROMedS algorithm.
*/
public class PROMedSFundamentalMatrixRobustEstimator extends FundamentalMatrixRobustEstimator {
/**
* Default non-robust method to estimate a fundamental matrix.
*/
public static final FundamentalMatrixEstimatorMethod DEFAULT_PROMEDS_FUNDAMENTAL_MATRIX_ESTIMATOR_METHOD =
FundamentalMatrixEstimatorMethod.SEVEN_POINTS_ALGORITHM;
/**
* 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.
* The stop threshold can be used to prevent the LMedS 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.
*/
public static final double DEFAULT_STOP_THRESHOLD = 1e-3;
/**
* Minimum allowed stop threshold value.
*/
public static final double MIN_STOP_THRESHOLD = 0.0;
/**
* 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 LMedS 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.
*/
private double stopThreshold;
/**
* Quality scores corresponding to each provided point.
* The larger the score value the better the quality of the sample.
*/
private double[] qualityScores;
/**
* Constructor.
*
* @param fundMatrixEstimatorMethod method for non-robust fundamental matrix
* estimator.
*/
public PROMedSFundamentalMatrixRobustEstimator(final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod) {
super(fundMatrixEstimatorMethod);
stopThreshold = DEFAULT_STOP_THRESHOLD;
}
/**
* Constructor.
*
* @param fundMatrixEstimatorMethod method for non-robust fundamental matrix
* estimator.
* @param listener listener to be notified of events such as when
* estimation starts, ends or its progress significantly changes.
*/
public PROMedSFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod,
final FundamentalMatrixRobustEstimatorListener listener) {
super(fundMatrixEstimatorMethod, listener);
stopThreshold = DEFAULT_STOP_THRESHOLD;
}
/**
* Constructor.
*
* @param fundMatrixEstimatorMethod method for non-robust fundamental matrix
* estimator.
* @param leftPoints 2D points on left view.
* @param rightPoints 2D points on right view.
* @throws IllegalArgumentException if provided list of points do not have
* the same length or their length is less than 8 points.
*/
public PROMedSFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod,
final List<Point2D> leftPoints, final List<Point2D> rightPoints) {
super(fundMatrixEstimatorMethod, leftPoints, rightPoints);
if (leftPoints.size() < EightPointsFundamentalMatrixEstimator.MIN_REQUIRED_POINTS) {
throw new IllegalArgumentException();
}
stopThreshold = DEFAULT_STOP_THRESHOLD;
}
/**
* Constructor.
*
* @param fundMatrixEstimatorMethod method for non-robust fundamental matrix
* estimator.
* @param leftPoints 2D points on left view.
* @param rightPoints 2D points on right view.
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @throws IllegalArgumentException if provided list of points do not have
* the same length or their length is less than 8 points.
*/
public PROMedSFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod,
final List<Point2D> leftPoints, final List<Point2D> rightPoints,
final FundamentalMatrixRobustEstimatorListener listener) {
super(fundMatrixEstimatorMethod, leftPoints, rightPoints, listener);
if (leftPoints.size() < EightPointsFundamentalMatrixEstimator.MIN_REQUIRED_POINTS) {
throw new IllegalArgumentException();
}
stopThreshold = DEFAULT_STOP_THRESHOLD;
}
/**
* Constructor.
*
* @param fundMatrixEstimatorMethod method for non-robust fundamental matrix
* estimator.
* @param qualityScores quality scores corresponding to each provided pair
* of matched points.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than required size (i.e. 7 matched pair of points).
*/
public PROMedSFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod, final double[] qualityScores) {
this(fundMatrixEstimatorMethod);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param fundMatrixEstimatorMethod method for non-robust fundamental matrix
* estimator.
* @param qualityScores quality scores corresponding to each provided pair
* of matched points.
* @param 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 size (i.e. 7 matched pair of points).
*/
public PROMedSFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod, final double[] qualityScores,
final FundamentalMatrixRobustEstimatorListener listener) {
this(fundMatrixEstimatorMethod, listener);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param fundMatrixEstimatorMethod method for non-robust fundamental matrix
* estimator.
* @param qualityScores quality scores corresponding to each provided pair
* of matched points.
* @param leftPoints 2D points on left view.
* @param rightPoints 2D points on right view.
* @throws IllegalArgumentException if provided list of points or quality
* scores do not have the same length or their length is less
* than 7 points.
*/
public PROMedSFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod, final double[] qualityScores,
final List<Point2D> leftPoints, final List<Point2D> rightPoints) {
this(fundMatrixEstimatorMethod, leftPoints, rightPoints);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param fundMatrixEstimatorMethod method for non-robust fundamental matrix
* estimator.
* @param qualityScores quality scores corresponding to each provided pair
* of matched points.
* @param leftPoints 2D points on left view.
* @param rightPoints 2D points on right view.
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @throws IllegalArgumentException if provided list of points or quality
* scores do not have the same length or their length is less
* than 7 points.
*/
public PROMedSFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod, final double[] qualityScores,
final List<Point2D> leftPoints, final List<Point2D> rightPoints,
final FundamentalMatrixRobustEstimatorListener listener) {
this(fundMatrixEstimatorMethod, leftPoints, rightPoints, listener);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*/
public PROMedSFundamentalMatrixRobustEstimator() {
this(DEFAULT_PROMEDS_FUNDAMENTAL_MATRIX_ESTIMATOR_METHOD);
}
/**
* Constructor.
*
* @param listener listener to be notified of events such as when
* estimation starts, ends or its progress significantly changes.
*/
public PROMedSFundamentalMatrixRobustEstimator(final FundamentalMatrixRobustEstimatorListener listener) {
this(DEFAULT_PROMEDS_FUNDAMENTAL_MATRIX_ESTIMATOR_METHOD, listener);
}
/**
* Constructor.
*
* @param leftPoints 2D points on left view.
* @param rightPoints 2D points on right view.
* @throws IllegalArgumentException if provided list of points do not have
* the same length or their length is less than 8 points.
*/
public PROMedSFundamentalMatrixRobustEstimator(final List<Point2D> leftPoints, final List<Point2D> rightPoints) {
this(DEFAULT_PROMEDS_FUNDAMENTAL_MATRIX_ESTIMATOR_METHOD, leftPoints, rightPoints);
}
/**
* Constructor.
*
* @param leftPoints 2D points on left view.
* @param rightPoints 2D points on right view.
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @throws IllegalArgumentException if provided list of points do not have
* the same length or their length is less than 8 points.
*/
public PROMedSFundamentalMatrixRobustEstimator(final List<Point2D> leftPoints, final List<Point2D> rightPoints,
final FundamentalMatrixRobustEstimatorListener listener) {
this(DEFAULT_PROMEDS_FUNDAMENTAL_MATRIX_ESTIMATOR_METHOD, leftPoints, rightPoints, listener);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided pair
* of matched points.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than required size (i.e. 7 matched pair of points).
*/
public PROMedSFundamentalMatrixRobustEstimator(final double[] qualityScores) {
this(DEFAULT_PROMEDS_FUNDAMENTAL_MATRIX_ESTIMATOR_METHOD, qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided pair
* of matched points.
* @param 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 size (i.e. 7 matched pair of points).
*/
public PROMedSFundamentalMatrixRobustEstimator(
final double[] qualityScores, final FundamentalMatrixRobustEstimatorListener listener) {
this(DEFAULT_PROMEDS_FUNDAMENTAL_MATRIX_ESTIMATOR_METHOD, qualityScores, listener);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided pair
* of matched points.
* @param leftPoints 2D points on left view.
* @param rightPoints 2D points on right view.
* @throws IllegalArgumentException if provided list of points or quality
* scores do not have the same length or their length is less
* than 7 points.
*/
public PROMedSFundamentalMatrixRobustEstimator(
final double[] qualityScores, final List<Point2D> leftPoints, final List<Point2D> rightPoints) {
this(DEFAULT_PROMEDS_FUNDAMENTAL_MATRIX_ESTIMATOR_METHOD, qualityScores, leftPoints, rightPoints);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided pair
* of matched points.
* @param leftPoints 2D points on left view.
* @param rightPoints 2D points on right view.
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @throws IllegalArgumentException if provided list of points or quality
* scores do not have the same length or their length is less
* than 7 points.
*/
public PROMedSFundamentalMatrixRobustEstimator(
final double[] qualityScores, final List<Point2D> leftPoints, final List<Point2D> rightPoints,
final FundamentalMatrixRobustEstimatorListener listener) {
this(DEFAULT_PROMEDS_FUNDAMENTAL_MATRIX_ESTIMATOR_METHOD, qualityScores, leftPoints, rightPoints, listener);
}
/**
* Sets matched 2D points on both left and right views.
*
* @param leftPoints matched 2D points on left view.
* @param rightPoints matched 2D points on right view.
* @throws LockedException if this fundamental matrix estimator is locked.
* @throws IllegalArgumentException if provided matched points on left and
* right views do not have the same length or if their length is
* less than 8 points.
*/
@Override
public void setPoints(final List<Point2D> leftPoints, final List<Point2D> rightPoints) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
if (leftPoints.size() < EightPointsFundamentalMatrixEstimator.MIN_REQUIRED_POINTS) {
throw new IllegalArgumentException();
}
super.setPoints(leftPoints, rightPoints);
}
/**
* 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 LMedS 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.
*
* @return stop threshold to stop the algorithm prematurely when a certain
* accuracy has been reached.
*/
public double getStopThreshold() {
return 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.
* 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 LMedS 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.
*
* @param stopThreshold stop threshold to stop the algorithm prematurely
* when a certain accuracy has been reached.
* @throws IllegalArgumentException if provided value is zero or negative.
* @throws LockedException if robust estimator is locked because an
* estimation is already in progress.
*/
public void setStopThreshold(final double stopThreshold) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
if (stopThreshold <= MIN_STOP_THRESHOLD) {
throw new IllegalArgumentException();
}
this.stopThreshold = stopThreshold;
}
/**
* Returns quality scores corresponding to each provided pair of points.
* The larger the score value the better the quality of the sampled matched
* pair of points.
*
* @return quality scores corresponding to each pair of points.
*/
@Override
public double[] getQualityScores() {
return qualityScores;
}
/**
* Sets quality scores corresponding to each provided pair of points.
* The larger the score value the better the quality of the sampled matched
* pair of points.
*
* @param qualityScores quality scores corresponding to each pair of points.
* @throws LockedException if robust estimator is locked because an
* estimation is already in progress.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than MINIMUM_SIZE (i.e. 3 samples).
*/
@Override
public void setQualityScores(final double[] qualityScores) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
internalSetQualityScores(qualityScores);
}
/**
* Returns value indicating whether required data has been provided so that
* fundamental matrix estimation can start.
* This is true when input data (i.e. 7 pairs of matched 2D points and their
* quality scores) are provided.
* If true, estimator is ready to compute a fundamental matrix, otherwise
* more data needs to be provided.
*
* @return true if estimator is ready, false otherwise.
*/
@Override
public boolean isReady() {
return super.isReady() && qualityScores != null && qualityScores.length == leftPoints.size();
}
/**
* Estimates a radial distortion using a robust estimator and
* the best set of matched 2D points found using the robust estimator.
*
* @return a radial distortion.
* @throws LockedException if robust estimator is locked because an
* estimation is already in progress.
* @throws NotReadyException if provided input data is not enough to start
* the estimation.
* @throws RobustEstimatorException if estimation fails for any reason
* (i.e. numerical instability, no solution available, etc).
*/
@SuppressWarnings("DuplicatedCode")
@Override
public FundamentalMatrix estimate() throws LockedException, NotReadyException, RobustEstimatorException {
if (isLocked()) {
throw new LockedException();
}
if (!isReady()) {
throw new NotReadyException();
}
final var innerEstimator = new PROMedSRobustEstimator<FundamentalMatrix>(
new PROMedSRobustEstimatorListener<>() {
// subset of left points
private final List<Point2D> subsetLeftPoints = new ArrayList<>();
// subset of right points
private final List<Point2D> subsetRightPoints = new ArrayList<>();
@Override
public double getThreshold() {
return stopThreshold;
}
@Override
public int getTotalSamples() {
return leftPoints.size();
}
@Override
public int getSubsetSize() {
return getMinRequiredPoints();
}
@Override
public void estimatePreliminarSolutions(
final int[] samplesIndices, final List<FundamentalMatrix> solutions) {
subsetLeftPoints.clear();
subsetRightPoints.clear();
for (final var samplesIndex : samplesIndices) {
subsetLeftPoints.add(leftPoints.get(samplesIndex));
subsetRightPoints.add(rightPoints.get(samplesIndex));
}
nonRobustEstimate(solutions, subsetLeftPoints, subsetRightPoints);
}
@Override
public double computeResidual(final FundamentalMatrix currentEstimation, final int i) {
final var leftPoint = leftPoints.get(i);
final var rightPoint = rightPoints.get(i);
return residual(currentEstimation, leftPoint, rightPoint);
}
@Override
public boolean isReady() {
return PROMedSFundamentalMatrixRobustEstimator.this.isReady();
}
@Override
public void onEstimateStart(final RobustEstimator<FundamentalMatrix> estimator) {
if (listener != null) {
listener.onEstimateStart(PROMedSFundamentalMatrixRobustEstimator.this);
}
}
@Override
public void onEstimateEnd(final RobustEstimator<FundamentalMatrix> estimator) {
if (listener != null) {
listener.onEstimateEnd(PROMedSFundamentalMatrixRobustEstimator.this);
}
}
@Override
public void onEstimateNextIteration(
final RobustEstimator<FundamentalMatrix> estimator, final int iteration) {
if (listener != null) {
listener.onEstimateNextIteration(
PROMedSFundamentalMatrixRobustEstimator.this, iteration);
}
}
@Override
public void onEstimateProgressChange(
final RobustEstimator<FundamentalMatrix> estimator, final float progress) {
if (listener != null) {
listener.onEstimateProgressChange(
PROMedSFundamentalMatrixRobustEstimator.this, progress);
}
}
@Override
public double[] getQualityScores() {
return qualityScores;
}
});
try {
locked = true;
inliersData = null;
innerEstimator.setConfidence(confidence);
innerEstimator.setMaxIterations(maxIterations);
innerEstimator.setProgressDelta(progressDelta);
final var result = innerEstimator.estimate();
inliersData = innerEstimator.getInliersData();
return attemptRefine(result);
} catch (final com.irurueta.numerical.LockedException e) {
throw new LockedException(e);
} catch (final com.irurueta.numerical.NotReadyException e) {
throw new NotReadyException(e);
} finally {
locked = false;
}
}
/**
* Returns method being used for robust estimation.
*
* @return method being used for robust estimation.
*/
@Override
public RobustEstimatorMethod getMethod() {
return RobustEstimatorMethod.PROMEDS;
}
/**
* 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.
*
* @return standard deviation used for refinement.
*/
@Override
protected double getRefinementStandardDeviation() {
final var inliersData = (PROMedSRobustEstimator.PROMedSInliersData) getInliersData();
return inliersData.getEstimatedThreshold();
}
/**
* Sets quality scores corresponding to each provided pair of matched
* points.
* This method is used internally and does not check whether instance is
* locked or not.
*
* @param qualityScores quality scores to be set.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than 8 points.
*/
private void internalSetQualityScores(final double[] qualityScores) {
if (qualityScores.length < getMinRequiredPoints()) {
throw new IllegalArgumentException();
}
this.qualityScores = qualityScores;
}
}