PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator.java
/*
* Copyright (C) 2017 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.geometry.estimators;
import com.irurueta.geometry.CoordinatesType;
import com.irurueta.geometry.PinholeCamera;
import com.irurueta.geometry.Point2D;
import com.irurueta.geometry.Point3D;
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 pinhole camera for provided collections of matched 2D/3D
* points using PROMedS + UPnP algorithms.
*/
@SuppressWarnings("DuplicatedCode")
public class PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator extends
UPnPPointCorrespondencePinholeCameraRobustEstimator {
/**
* 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 = 1.0;
/**
* 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 pair of matched points.
* The larger the score value the better the quality of the matching.
*/
private double[] qualityScores;
/**
* Constructor.
*/
public PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator() {
super();
stopThreshold = DEFAULT_STOP_THRESHOLD;
}
/**
* Constructor with lists of points to be used to estimate a pinhole camera.
* 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 MIN_NUMBER_OF_POINT_CORRESPONDENCES.
*
* @param points3D list of 3D points used to estimate a pinhole camera.
* @param points2D list of corresponding projected 2D points used to
* estimate a pinhole camera.
* @throws IllegalArgumentException if provided lists of points don't have
* the same size or their size is smaller than required minimum size
* (6 correspondences).
*/
public PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator(
final List<Point3D> points3D, final List<Point2D> points2D) {
super(points3D, points2D);
stopThreshold = DEFAULT_STOP_THRESHOLD;
}
/**
* Constructor.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
*/
public PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator(
final PinholeCameraRobustEstimatorListener listener) {
super(listener);
stopThreshold = DEFAULT_STOP_THRESHOLD;
}
/**
* Constructor with listener and lists of points to be used ot estimate a
* pinhole camera.
* 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 MIN_NUMBER_OF_POINT_CORRESPONDENCES.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param points3D list of 3D points used to estimate a pinhole camera.
* @param points2D list of corresponding projected 2D points used to
* estimate a pinhole camera.
* @throws IllegalArgumentException if provided lists of points don't have
* the same size or their size is smaller than required minimum size
* (6 correspondences).
*/
public PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator(
final PinholeCameraRobustEstimatorListener listener,
final List<Point3D> points3D, final List<Point2D> points2D) {
super(listener, points3D, points2D);
stopThreshold = DEFAULT_STOP_THRESHOLD;
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each pair of matched
* points.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than MINIMUM_SIZE (i.e. 3 samples).
*/
public PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator(final double[] qualityScores) {
super();
stopThreshold = DEFAULT_STOP_THRESHOLD;
internalSetQualityScores(qualityScores);
}
/**
* Constructor with lists of points to be used to estimate a pinhole camera.
* 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 MIN_NUMBER_OF_POINT_CORRESPONDENCES.
*
* @param points3D list of 3D points used to estimate a pinhole camera.
* @param points2D list of corresponding projected 2D points used to
* estimate a pinhole camera.
* @param qualityScores quality scores corresponding to each pair of matched
* points.
* @throws IllegalArgumentException if provided lists of points and array
* of quality scores don't have the same size or their size is smaller than
* 6 correspondences.
*/
public PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator(
final List<Point3D> points3D, final List<Point2D> points2D, final double[] qualityScores) {
super(points3D, points2D);
if (qualityScores.length != points3D.size()) {
throw new IllegalArgumentException();
}
stopThreshold = DEFAULT_STOP_THRESHOLD;
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param qualityScores quality scores corresponding to each pair of matched
* points.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than MINIMUM_SIZE (i.e. 3 samples).
*/
public PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator(
final PinholeCameraRobustEstimatorListener listener, final double[] qualityScores) {
super(listener);
stopThreshold = DEFAULT_STOP_THRESHOLD;
internalSetQualityScores(qualityScores);
}
/**
* Constructor with listener and lists of points to be used ot estimate a
* pinhole camera.
* 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 MIN_NUMBER_OF_POINT_CORRESPONDENCES.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param points3D list of 3D points used to estimate a pinhole camera.
* @param points2D list of corresponding projected 2D points used to
* estimate a pinhole camera.
* @param qualityScores quality scores corresponding to each pair of matched
* points.
* @throws IllegalArgumentException if provided lists of points don't have
* the same size or their size is smaller than
* MIN_NUMBER_OF_POINT_CORRESPONDENCES.
*/
public PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator(
final PinholeCameraRobustEstimatorListener listener,
final List<Point3D> points3D, final List<Point2D> points2D, final double[] qualityScores) {
super(listener, points3D, points2D);
if (qualityScores.length != points3D.size()) {
throw new IllegalArgumentException();
}
stopThreshold = DEFAULT_STOP_THRESHOLD;
internalSetQualityScores(qualityScores);
}
/**
* 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.
* As in LMedS, 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.
*
* @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.
* As in LMedS, 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.
*
* @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 pair of matched points.
* The larger the score value the better the quality of the matching.
*
* @return quality scores corresponding to each pair of matched points.
*/
@Override
public double[] getQualityScores() {
return qualityScores;
}
/**
* Sets quality scores corresponding to each pair of matched points.
* The larger the score value the better the quality of the matching.
*
* @param qualityScores quality scores corresponding to each pair of matched
* 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. 6 samples).
*/
@Override
public void setQualityScores(final double[] qualityScores) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
internalSetQualityScores(qualityScores);
}
/**
* Indicates if estimator is ready to start the affine 2D transformation
* estimation.
* This is true when input data (i.e. lists of matched points and quality
* scores) are provided and a minimum of MINIMUM_SIZE points are available.
*
* @return true if estimator is ready, false otherwise.
*/
@Override
public boolean isReady() {
return super.isReady() && qualityScores != null && qualityScores.length == points3D.size();
}
/**
* Estimates an affine 2D transformation using a robust estimator and
* the best set of matched 2D point correspondences found using the robust
* estimator.
*
* @return an affine 2D transformation.
* @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).
*/
@Override
public PinholeCamera estimate() throws LockedException, NotReadyException, RobustEstimatorException {
if (isLocked()) {
throw new LockedException();
}
if (!isReady()) {
throw new NotReadyException();
}
// pinhole camera estimator using UPnP (Uncalibrated Perspective-n-Point) algorithm
final var nonRobustEstimator = new UPnPPointCorrespondencePinholeCameraEstimator();
nonRobustEstimator.setPlanarConfigurationAllowed(planarConfigurationAllowed);
nonRobustEstimator.setNullspaceDimension2Allowed(nullspaceDimension2Allowed);
nonRobustEstimator.setPlanarThreshold(planarThreshold);
nonRobustEstimator.setSkewness(skewness);
nonRobustEstimator.setHorizontalPrincipalPoint(horizontalPrincipalPoint);
nonRobustEstimator.setVerticalPrincipalPoint(verticalPrincipalPoint);
// suggestions
nonRobustEstimator.setSuggestSkewnessValueEnabled(isSuggestSkewnessValueEnabled());
nonRobustEstimator.setSuggestedSkewnessValue(getSuggestedSkewnessValue());
nonRobustEstimator.setSuggestHorizontalFocalLengthEnabled(isSuggestHorizontalFocalLengthEnabled());
nonRobustEstimator.setSuggestedHorizontalFocalLengthValue(getSuggestedHorizontalFocalLengthValue());
nonRobustEstimator.setSuggestVerticalFocalLengthEnabled(isSuggestVerticalFocalLengthEnabled());
nonRobustEstimator.setSuggestedVerticalFocalLengthValue(getSuggestedVerticalFocalLengthValue());
nonRobustEstimator.setSuggestAspectRatioEnabled(isSuggestAspectRatioEnabled());
nonRobustEstimator.setSuggestedAspectRatioValue(getSuggestedAspectRatioValue());
nonRobustEstimator.setSuggestPrincipalPointEnabled(isSuggestPrincipalPointEnabled());
nonRobustEstimator.setSuggestedPrincipalPointValue(getSuggestedPrincipalPointValue());
nonRobustEstimator.setSuggestRotationEnabled(isSuggestRotationEnabled());
nonRobustEstimator.setSuggestedRotationValue(getSuggestedRotationValue());
nonRobustEstimator.setSuggestCenterEnabled(isSuggestCenterEnabled());
nonRobustEstimator.setSuggestedCenterValue(getSuggestedCenterValue());
final var innerEstimator = new PROMedSRobustEstimator<>(new PROMedSRobustEstimatorListener<PinholeCamera>() {
// point to be reused when computing residuals
private final Point2D testPoint = Point2D.create(CoordinatesType.HOMOGENEOUS_COORDINATES);
// 3D points for a subset of samples
private final List<Point3D> subset3D = new ArrayList<>();
// 2D points for a subset of samples
private final List<Point2D> subset2D = new ArrayList<>();
@Override
public double getThreshold() {
return stopThreshold;
}
@Override
public int getTotalSamples() {
return points3D.size();
}
@Override
public int getSubsetSize() {
return PointCorrespondencePinholeCameraRobustEstimator.MIN_NUMBER_OF_POINT_CORRESPONDENCES;
}
@Override
public void estimatePreliminarSolutions(
final int[] samplesIndices, final List<PinholeCamera> solutions) {
subset3D.clear();
subset3D.add(points3D.get(samplesIndices[0]));
subset3D.add(points3D.get(samplesIndices[1]));
subset3D.add(points3D.get(samplesIndices[2]));
subset3D.add(points3D.get(samplesIndices[3]));
subset3D.add(points3D.get(samplesIndices[4]));
subset3D.add(points3D.get(samplesIndices[5]));
subset2D.clear();
subset2D.add(points2D.get(samplesIndices[0]));
subset2D.add(points2D.get(samplesIndices[1]));
subset2D.add(points2D.get(samplesIndices[2]));
subset2D.add(points2D.get(samplesIndices[3]));
subset2D.add(points2D.get(samplesIndices[4]));
subset2D.add(points2D.get(samplesIndices[5]));
try {
nonRobustEstimator.setLists(subset3D, subset2D);
final var cam = nonRobustEstimator.estimate();
solutions.add(cam);
} catch (final Exception e) {
// if points configuration is degenerate, no solution is
// added
}
}
@Override
public double computeResidual(final PinholeCamera currentEstimation, final int i) {
// pick i-th points
final var point3D = points3D.get(i);
final var point2D = points2D.get(i);
// project point3D into test point
currentEstimation.project(point3D, testPoint);
// compare test point and 2D point
return testPoint.distanceTo(point2D);
}
@Override
public boolean isReady() {
return PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator.this.isReady();
}
@Override
public void onEstimateStart(final RobustEstimator<PinholeCamera> estimator) {
if (listener != null) {
listener.onEstimateStart(
PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator.this);
}
}
@Override
public void onEstimateEnd(final RobustEstimator<PinholeCamera> estimator) {
if (listener != null) {
listener.onEstimateEnd(
PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator.this);
}
}
@Override
public void onEstimateNextIteration(
final RobustEstimator<PinholeCamera> estimator, final int iteration) {
if (listener != null) {
listener.onEstimateNextIteration(
PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator.this,
iteration);
}
}
@Override
public void onEstimateProgressChange(
final RobustEstimator<PinholeCamera> estimator, final float progress) {
if (listener != null) {
listener.onEstimateProgressChange(
PROMedSUPnPPointCorrespondencePinholeCameraRobustEstimator.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, nonRobustEstimator.getMaxSuggestionWeight());
} 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 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 MINIMUM_SIZE.
*/
private void internalSetQualityScores(final double[] qualityScores) {
if (qualityScores.length < MIN_NUMBER_OF_POINT_CORRESPONDENCES) {
throw new IllegalArgumentException();
}
this.qualityScores = qualityScores;
}
}