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BoofCV is an open source Java library for real-time computer vision and robotics applications.
/*
* Copyright (c) 2021, Peter Abeles. All Rights Reserved.
*
* This file is part of BoofCV (http://boofcv.org).
*
* 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 boofcv.abst.geo.triangulate;
import boofcv.abst.geo.RefineTriangulateEpipolar;
import boofcv.alg.geo.triangulate.ResidualsTriangulateEpipolarSampson;
import boofcv.misc.BoofMiscOps;
import georegression.struct.point.Point2D_F64;
import georegression.struct.point.Point3D_F64;
import lombok.Getter;
import lombok.Setter;
import org.ddogleg.optimization.FactoryOptimization;
import org.ddogleg.optimization.UnconstrainedLeastSquares;
import org.ejml.data.DMatrixRMaj;
import java.util.List;
/**
* Nonlinear least squares triangulation.
*
* @author Peter Abeles
*/
public class TriangulateRefineEpipolarLS implements RefineTriangulateEpipolar {
final @Getter ResidualsTriangulateEpipolarSampson func = new ResidualsTriangulateEpipolarSampson();
final @Getter UnconstrainedLeastSquares minimizer;
final double[] param = new double[3];
@Getter @Setter int maxIterations;
@Getter @Setter double convergenceTol;
public TriangulateRefineEpipolarLS( double convergenceTol, int maxIterations ) {
this.maxIterations = maxIterations;
this.convergenceTol = convergenceTol;
minimizer = FactoryOptimization.levenbergMarquardt(null, false);
BoofMiscOps.checkEq(3, func.getNumOfInputsN());
}
@Override
public boolean process( List observations,
List fundamentalWorldToCam,
Point3D_F64 worldPt, Point3D_F64 refinedPt ) {
func.setObservations(observations, fundamentalWorldToCam);
minimizer.setFunction(func, null);
// the parameter being optimized is the world point location
param[0] = worldPt.x;
param[1] = worldPt.y;
param[2] = worldPt.z;
minimizer.initialize(param, 0, convergenceTol*observations.size());
for (int i = 0; i < maxIterations; i++) {
if (minimizer.iterate())
break;
}
double[] found = minimizer.getParameters();
refinedPt.x = found[0];
refinedPt.y = found[1];
refinedPt.z = found[2];
return true;
}
}
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