InhomogeneousPoint3DRefiner.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.refiners;
import com.irurueta.algebra.Matrix;
import com.irurueta.geometry.InhomogeneousPoint3D;
import com.irurueta.geometry.Plane;
import com.irurueta.geometry.estimators.LockedException;
import com.irurueta.geometry.estimators.NotReadyException;
import com.irurueta.numerical.EvaluationException;
import com.irurueta.numerical.GradientEstimator;
import com.irurueta.numerical.fitting.LevenbergMarquardtMultiDimensionFitter;
import com.irurueta.numerical.fitting.LevenbergMarquardtMultiDimensionFunctionEvaluator;
import com.irurueta.numerical.robust.InliersData;
import java.util.BitSet;
import java.util.List;
/**
* Refines an inhomogeneous 3D point by taking into account an initial
* estimation, inlier samples and their residuals.
* This class can be used to find a solution that minimizes error of inliers in
* LMSE terms.
* Typically, a refiner is used by a robust estimator, however it can also be
* useful in some other situations.
*/
@SuppressWarnings("DuplicatedCode")
public class InhomogeneousPoint3DRefiner extends Point3DRefiner<InhomogeneousPoint3D> {
/**
* Constructor.
*/
public InhomogeneousPoint3DRefiner() {
}
/**
* Constructor.
*
* @param initialEstimation initial estimation to be set.
* @param keepCovariance true if covariance of estimation must be kept after
* refinement, false otherwise.
* @param inliers set indicating which of the provided matches are inliers.
* @param residuals residuals for matched samples.
* @param numInliers number of inliers on initial estimation.
* @param samples collection of samples.
* @param refinementStandardDeviation standard deviation used for
* Levenberg-Marquardt fitting.
*/
public InhomogeneousPoint3DRefiner(
final InhomogeneousPoint3D initialEstimation, final boolean keepCovariance, final BitSet inliers,
final double[] residuals, final int numInliers, final List<Plane> samples,
final double refinementStandardDeviation) {
super(initialEstimation, keepCovariance, inliers, residuals, numInliers, samples, refinementStandardDeviation);
}
/**
* Constructor.
*
* @param initialEstimation initial estimation to be set.
* @param keepCovariance true if covariance of estimation must be kept after
* refinement, false otherwise.
* @param inliersData inlier data, typically obtained from a robust
* estimator.
* @param samples collection of samples.
* @param refinementStandardDeviation standard deviation used for
* Levenberg-Marquardt fitting.
*/
public InhomogeneousPoint3DRefiner(
final InhomogeneousPoint3D initialEstimation, final boolean keepCovariance, final InliersData inliersData,
final List<Plane> samples, final double refinementStandardDeviation) {
super(initialEstimation, keepCovariance, inliersData, samples, refinementStandardDeviation);
}
/**
* Refines provided initial estimation.
*
* @return refined estimation.
* @throws NotReadyException if not enough input data has been provided.
* @throws LockedException if estimator is locked because refinement is
* already in progress.
* @throws RefinerException if refinement fails for some reason (e.g. unable
* to converge to a result).
*/
@Override
public InhomogeneousPoint3D refine() throws NotReadyException, LockedException, RefinerException {
final var result = new InhomogeneousPoint3D();
refine(result);
return result;
}
/**
* Refines provided initial estimation.
* This method always sets a value into provided result instance regardless
* of the fact that error has actually improved in LMSE terms or not.
*
* @param result instance where refined estimation will be stored.
* @return true if result improved (decreases) in LMSE terms respect to
* initial estimation, false if no improvement has been achieved.
* @throws NotReadyException if not enough input data has been provided.
* @throws LockedException if estimator is locked because refinement is
* already in progress.
* @throws RefinerException if refinement fails for some reason (e.g. unable
* to converge to a result).
*/
@Override
public boolean refine(final InhomogeneousPoint3D result) throws NotReadyException, LockedException,
RefinerException {
if (isLocked()) {
throw new LockedException();
}
if (!isReady()) {
throw new NotReadyException();
}
locked = true;
if (listener != null) {
listener.onRefineStart(this, initialEstimation);
}
final var initialTotalResidual = totalResidual(initialEstimation);
try {
final var initParams = initialEstimation.asArray();
// output values to be fitted/optimized will contain residuals
final var y = new double[numInliers];
// input values will contain planes to compute residuals
final var nDims = Plane.PLANE_NUMBER_PARAMS;
final var x = new Matrix(numInliers, nDims);
final var nSamples = inliers.length();
var pos = 0;
for (var i = 0; i < nSamples; i++) {
if (inliers.get(i)) {
// sample is inlier
final var plane = samples.get(i);
plane.normalize();
x.setElementAt(pos, 0, plane.getA());
x.setElementAt(pos, 1, plane.getB());
x.setElementAt(pos, 2, plane.getC());
x.setElementAt(pos, 3, plane.getD());
y[pos] = residuals[i];
pos++;
}
}
final var evaluator = new LevenbergMarquardtMultiDimensionFunctionEvaluator() {
private final Plane plane = new Plane();
private final InhomogeneousPoint3D point = new InhomogeneousPoint3D();
private final GradientEstimator gradientEstimator = new GradientEstimator(p -> {
this.point.setCoordinates(p);
return residual(this.point, plane);
});
@Override
public int getNumberOfDimensions() {
return nDims;
}
@Override
public double[] createInitialParametersArray() {
return initParams;
}
@Override
public double evaluate(final int i, final double[] point, final double[] params,
final double[] derivatives) throws EvaluationException {
// point contains a,b,c,d values for plane
plane.setParameters(point);
// params contains coordinates of point
this.point.setCoordinates(params);
final var y = residual(this.point, plane);
gradientEstimator.gradient(params, derivatives);
return y;
}
};
final var fitter = new LevenbergMarquardtMultiDimensionFitter(evaluator, x, y,
getRefinementStandardDeviation());
fitter.fit();
// obtain estimated params
final var params = fitter.getA();
// update point
result.setCoordinates(params);
if (keepCovariance) {
// keep covariance
covariance = fitter.getCovar();
}
final var finalTotalResidual = totalResidual(result);
final var errorDecreased = finalTotalResidual < initialTotalResidual;
if (listener != null) {
listener.onRefineEnd(this, initialEstimation, result, errorDecreased);
}
return errorDecreased;
} catch (final Exception e) {
throw new RefinerException(e);
} finally {
locked = false;
}
}
}