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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.sfm;
import com.irurueta.geometry.CoordinatesType;
import com.irurueta.geometry.PinholeCamera;
import com.irurueta.geometry.Point2D;
import com.irurueta.geometry.Point3D;
import com.irurueta.geometry.estimators.LockedException;
import com.irurueta.geometry.estimators.NotReadyException;
import com.irurueta.numerical.robust.PROSACRobustEstimator;
import com.irurueta.numerical.robust.PROSACRobustEstimatorListener;
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;
/**
* Robustly triangulates 3D points from matched 2D points and their
* corresponding cameras on several views using PROSAC algorithm.
*/
public class PROSACRobustSinglePoint3DTriangulator extends
RobustSinglePoint3DTriangulator {
/**
* Constant defining default threshold to determine whether samples are
* inliers or not.
* By default 1.0 is considered a good value for cases where 2D point
* measures are done on 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 samples are inliers or not when testing
* possible estimation solutions.
* The threshold refers to the amount of projection error (i.e. distance of
* projected solution using each camera).
*/
private double mThreshold;
/**
* Quality scores corresponding to each provided view.
* The larger the score value the better the quality of the sample.
*/
private double[] mQualityScores;
/**
* Constructor.
*/
public PROSACRobustSinglePoint3DTriangulator() {
super();
mThreshold = DEFAULT_THRESHOLD;
}
/**
* Constructor.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
*/
public PROSACRobustSinglePoint3DTriangulator(
final RobustSinglePoint3DTriangulatorListener listener) {
super(listener);
mThreshold = DEFAULT_THRESHOLD;
}
/**
* Constructor.
*
* @param points Matched 2D points. Each point in the list is assumed to be
* projected by the corresponding camera in the list.
* @param cameras List of cameras associated to the matched 2D point on the
* same position as the camera on the list.
* @throws IllegalArgumentException if provided lists don't have the same
* length or their length is less than 2 views, which is the minimum
* required to compute triangulation.
*/
public PROSACRobustSinglePoint3DTriangulator(final List points,
final List cameras) {
super(points, cameras);
mThreshold = DEFAULT_THRESHOLD;
}
/**
* Constructor.
*
* @param points Matched 2D points. Each point in the list is assumed to be
* projected by the corresponding camera in the list.
* @param cameras List of cameras associated to the matched 2D point on the
* same position as the camera on the list.
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @throws IllegalArgumentException if provided lists don't have the same
* length or their length is less than 2 views, which is the minimum
* required to compute triangulation.
*/
public PROSACRobustSinglePoint3DTriangulator(final List points,
final List cameras,
final RobustSinglePoint3DTriangulatorListener listener) {
super(points, cameras, listener);
mThreshold = DEFAULT_THRESHOLD;
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided view.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than required size (i.e. 2 views).
*/
public PROSACRobustSinglePoint3DTriangulator(final double[] qualityScores) {
this();
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided view.
* @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. 2 views).
*/
public PROSACRobustSinglePoint3DTriangulator(final double[] qualityScores,
final RobustSinglePoint3DTriangulatorListener listener) {
this(listener);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param points Matched 2D points. Each point in the list is assumed to be
* projected by the corresponding camera in the list.
* @param cameras List of cameras associated to the matched 2D point on the
* same position as the camera on the list.
* @param qualityScores quality scores corresponding to each provided view.
* @throws IllegalArgumentException if provided lists or quality scores
* don't have the same length or their length is less than 2 views, which
* is the minimum required to compute triangulation.
*/
public PROSACRobustSinglePoint3DTriangulator(final List points,
final List cameras,
final double[] qualityScores) {
this(points, cameras);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param points Matched 2D points. Each point in the list is assumed to be
* projected by the corresponding camera in the list.
* @param cameras List of cameras associated to the matched 2D point on the
* same position as the camera on the list.
* @param qualityScores quality scores corresponding to each provided view.
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @throws IllegalArgumentException if provided lists or quality scores
* don't have the same length or their length is less than 2 views, which is
* the minimum required to compute triangulation.
*/
public PROSACRobustSinglePoint3DTriangulator(final List points,
final List cameras,
final double[] qualityScores,
final RobustSinglePoint3DTriangulatorListener listener) {
this(points, cameras, listener);
internalSetQualityScores(qualityScores);
}
/**
* 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 projected 2D points.
*
* @return threshold to determine whether points are inliers or not when
* testing possible estimation solutions.
*/
public double getThreshold() {
return mThreshold;
}
/**
* 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 projected 2D points.
*
* @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;
}
/**
* Returns quality scores corresponding to each provided view.
* The larger the score value the better the quality of the sampled view.
*
* @return quality scores corresponding to each view.
*/
@Override
public double[] getQualityScores() {
return mQualityScores;
}
/**
* Sets quality scores corresponding to each provided view.
* The larger the score value the better the quality of the sampled view.
*
* @param qualityScores quality scores corresponding to each view.
* @throws LockedException if robust estimator is locked because an
* estimation is already in progress.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than MIN_REQUIRED_VIEWS (i.e. 2 views).
*/
@Override
public void setQualityScores(final double[] qualityScores) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
internalSetQualityScores(qualityScores);
}
/**
* Indicates if triangulator is ready to start the 3D point triangulation.
* This is true when input data (i.e. 2D points, cameras and quality scores)
* are provided and a minimum of 2 views are available.
*
* @return true if estimator is ready, false otherwise.
*/
@Override
public boolean isReady() {
return super.isReady() && mQualityScores != null &&
mQualityScores.length == mPoints2D.size();
}
/**
* Triangulates provided matched 2D points being projected by each
* corresponding camera into a single 3D point.
* At least 2 matched 2D points and their corresponding 2 cameras are
* required to compute triangulation. If more views are provided, an
* averaged solution can be found.
*
* @return computed triangulated 3D point.
* @throws LockedException if this instance is locked.
* @throws NotReadyException if lists of points and cameras don't have the
* same length or less than 2 views are provided.
* @throws RobustEstimatorException if estimation fails for any reason
* (i.e. numerical instability, no solution available, etc).
*/
@SuppressWarnings("DuplicatedCode")
@Override
public Point3D triangulate() throws LockedException, NotReadyException,
RobustEstimatorException {
if (isLocked()) {
throw new LockedException();
}
if (!isReady()) {
throw new NotReadyException();
}
final PROSACRobustEstimator innerEstimator =
new PROSACRobustEstimator<>(
new PROSACRobustEstimatorListener() {
// point to be reused when computing residuals
private final Point2D mTestPoint = Point2D.create(
CoordinatesType.HOMOGENEOUS_COORDINATES);
// non-robust 3D point triangulator
private final SinglePoint3DTriangulator mTriangulator =
SinglePoint3DTriangulator.create(mUseHomogeneousSolution ?
Point3DTriangulatorType.LMSE_HOMOGENEOUS_TRIANGULATOR :
Point3DTriangulatorType.LMSE_INHOMOGENEOUS_TRIANGULATOR);
// subset of 2D points
private final List mSubsetPoints = new ArrayList<>();
// subset of cameras
private final List mSubsetCameras =
new ArrayList<>();
@Override
public double getThreshold() {
return mThreshold;
}
@Override
public int getTotalSamples() {
return mPoints2D.size();
}
@Override
public int getSubsetSize() {
return MIN_REQUIRED_VIEWS;
}
@Override
public void estimatePreliminarSolutions(final int[] samplesIndices,
final List solutions) {
mSubsetPoints.clear();
mSubsetPoints.add(mPoints2D.get(samplesIndices[0]));
mSubsetPoints.add(mPoints2D.get(samplesIndices[1]));
mSubsetCameras.clear();
mSubsetCameras.add(mCameras.get(samplesIndices[0]));
mSubsetCameras.add(mCameras.get(samplesIndices[1]));
try {
mTriangulator.setPointsAndCameras(mSubsetPoints,
mSubsetCameras);
final Point3D triangulated = mTriangulator.triangulate();
solutions.add(triangulated);
} catch (final Exception e) {
// if anything fails, no solution is added
}
}
@Override
public double computeResidual(final Point3D currentEstimation, final int i) {
final Point2D point2D = mPoints2D.get(i);
final PinholeCamera camera = mCameras.get(i);
// project estimated point with camera
camera.project(currentEstimation, mTestPoint);
// return distance of projected point respect to the original one
// as a residual
return mTestPoint.distanceTo(point2D);
}
@Override
public boolean isReady() {
return PROSACRobustSinglePoint3DTriangulator.this.isReady();
}
@Override
public void onEstimateStart(final RobustEstimator estimator) {
if (mListener != null) {
mListener.onTriangulateStart(
PROSACRobustSinglePoint3DTriangulator.this);
}
}
@Override
public void onEstimateEnd(final RobustEstimator estimator) {
if (mListener != null) {
mListener.onTriangulateEnd(
PROSACRobustSinglePoint3DTriangulator.this);
}
}
@Override
public void onEstimateNextIteration(
final RobustEstimator estimator, final int iteration) {
if (mListener != null) {
mListener.onTriangulateNextIteration(
PROSACRobustSinglePoint3DTriangulator.this,
iteration);
}
}
@Override
public void onEstimateProgressChange(
final RobustEstimator estimator, final float progress) {
if (mListener != null) {
mListener.onTriangulateProgressChange(
PROSACRobustSinglePoint3DTriangulator.this,
progress);
}
}
@Override
public double[] getQualityScores() {
return mQualityScores;
}
});
try {
mLocked = true;
innerEstimator.setConfidence(mConfidence);
innerEstimator.setMaxIterations(mMaxIterations);
innerEstimator.setProgressDelta(mProgressDelta);
return innerEstimator.estimate();
} 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.PROSAC;
}
/**
* Sets quality scores corresponding to each provided view.
* 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_REQUIRED_VIEWS) {
throw new IllegalArgumentException();
}
mQualityScores = qualityScores;
}
}
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