com.irurueta.ar.epipolar.estimators.MSACFundamentalMatrixRobustEstimator Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of irurueta-ar Show documentation
Show all versions of irurueta-ar Show documentation
Augmented Reality and 3D reconstruction library
/*
* Copyright (C) 2015 Alberto Irurueta Carro ([email protected])
*
* 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.MSACRobustEstimator;
import com.irurueta.numerical.robust.MSACRobustEstimatorListener;
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 RANSAC algorithm.
*/
public class MSACFundamentalMatrixRobustEstimator extends
FundamentalMatrixRobustEstimator {
/**
* 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 in pixels, since typically the minimum resolution is 1 pixel.
*/
public static final double DEFAULT_THRESHOLD = 1.0;
/**
* Minimum value that can be set as threshold.
* Threshold must be strictly greater than 0.0.
*/
public static final double MIN_THRESHOLD = 0.0;
/**
* Threshold to determine whether pairs of matched points are inliers or not
* when testing possible estimation solutions.
* The threshold refers to the amount of error (i.e. distance) a given
* point has respect to the epipolar line generated by its matched point.
*/
private double mThreshold;
/**
* Constructor.
*
* @param fundMatrixEstimatorMethod method for non-robust fundamental matrix
* estimator.
*/
public MSACFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod) {
super(fundMatrixEstimatorMethod);
mThreshold = DEFAULT_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 MSACFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod,
final FundamentalMatrixRobustEstimatorListener listener) {
super(fundMatrixEstimatorMethod, listener);
mThreshold = DEFAULT_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 7 points.
*/
public MSACFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod,
final List leftPoints, final List rightPoints) {
super(fundMatrixEstimatorMethod, leftPoints, rightPoints);
mThreshold = DEFAULT_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 7 points.
*/
public MSACFundamentalMatrixRobustEstimator(
final FundamentalMatrixEstimatorMethod fundMatrixEstimatorMethod,
final List leftPoints, final List rightPoints,
final FundamentalMatrixRobustEstimatorListener listener) {
super(fundMatrixEstimatorMethod, leftPoints, rightPoints, listener);
mThreshold = DEFAULT_THRESHOLD;
}
/**
* Constructor.
*/
public MSACFundamentalMatrixRobustEstimator() {
this(DEFAULT_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 MSACFundamentalMatrixRobustEstimator(
final FundamentalMatrixRobustEstimatorListener listener) {
this(DEFAULT_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 7 points.
*/
public MSACFundamentalMatrixRobustEstimator(final List leftPoints,
final List rightPoints) {
this(DEFAULT_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 7 points.
*/
public MSACFundamentalMatrixRobustEstimator(final List leftPoints,
final List rightPoints,
final FundamentalMatrixRobustEstimatorListener listener) {
this(DEFAULT_FUNDAMENTAL_MATRIX_ESTIMATOR_METHOD, leftPoints,
rightPoints, listener);
}
/**
* Returns threshold to determine whether matched pairs of points are
* inliers or not when testing possible estimation solutions.
* The threshold refers to the amount of error (i.e. distance) a given
* point has respect to the epipolar line generated by its matched point.
*
* @return threshold to determine whether matched pairs of points are
* inliers or not.
*/
public double getThreshold() {
return mThreshold;
}
/**
* Sets threshold to determine whether matched pairs of points are inliers
* or not when testing possible estimation solutions.
*
* @param threshold threshold to be set.
* @throws IllegalArgumentException if provided value is equal or less than
* zero.
* @throws LockedException if robust estimator is locked because an
* estimation is already in progress.
*/
public void setThreshold(final double threshold) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
if (threshold <= MIN_THRESHOLD) {
throw new IllegalArgumentException();
}
mThreshold = threshold;
}
/**
* 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 MSACRobustEstimator innerEstimator =
new MSACRobustEstimator<>(
new MSACRobustEstimatorListener() {
// subset of left points
private final List mSubsetLeftPoints = new ArrayList<>();
// subset of right points
private final List mSubsetRightPoints = new ArrayList<>();
@Override
public double getThreshold() {
return mThreshold;
}
@Override
public int getTotalSamples() {
return mLeftPoints.size();
}
@Override
public int getSubsetSize() {
return getMinRequiredPoints();
}
@Override
public void estimatePreliminarSolutions(final int[] samplesIndices,
final List solutions) {
mSubsetLeftPoints.clear();
mSubsetRightPoints.clear();
for (final int samplesIndex : samplesIndices) {
mSubsetLeftPoints.add(mLeftPoints.get(samplesIndex));
mSubsetRightPoints.add(mRightPoints.get(samplesIndex));
}
nonRobustEstimate(solutions, mSubsetLeftPoints,
mSubsetRightPoints);
}
@Override
public double computeResidual(final FundamentalMatrix currentEstimation,
final int i) {
final Point2D leftPoint = mLeftPoints.get(i);
final Point2D rightPoint = mRightPoints.get(i);
return residual(currentEstimation, leftPoint, rightPoint);
}
@Override
public boolean isReady() {
return MSACFundamentalMatrixRobustEstimator.this.isReady();
}
@Override
public void onEstimateStart(
final RobustEstimator estimator) {
if (mListener != null) {
mListener.onEstimateStart(
MSACFundamentalMatrixRobustEstimator.this);
}
}
@Override
public void onEstimateEnd(
final RobustEstimator estimator) {
if (mListener != null) {
mListener.onEstimateEnd(
MSACFundamentalMatrixRobustEstimator.this);
}
}
@Override
public void onEstimateNextIteration(
final RobustEstimator estimator,
final int iteration) {
if (mListener != null) {
mListener.onEstimateNextIteration(
MSACFundamentalMatrixRobustEstimator.this,
iteration);
}
}
@Override
public void onEstimateProgressChange(
final RobustEstimator estimator,
final float progress) {
if (mListener != null) {
mListener.onEstimateProgressChange(
MSACFundamentalMatrixRobustEstimator.this,
progress);
}
}
});
try {
mLocked = true;
mInliersData = null;
innerEstimator.setConfidence(mConfidence);
innerEstimator.setMaxIterations(mMaxIterations);
innerEstimator.setProgressDelta(mProgressDelta);
FundamentalMatrix result = innerEstimator.estimate();
mInliersData = 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 {
mLocked = false;
}
}
/**
* Returns method being used for robust estimation.
*
* @return method being used for robust estimation.
*/
@Override
public RobustEstimatorMethod getMethod() {
return RobustEstimatorMethod.MSAC;
}
/**
* 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() {
return mThreshold;
}
}
© 2015 - 2025 Weber Informatics LLC | Privacy Policy