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BoofCV is an open source Java library for real-time computer vision and robotics applications.
/*
* Copyright (c) 2011-2018, 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.RefineTriangulateMetric;
import boofcv.alg.geo.triangulate.ResidualsTriangulateMetricSimple;
import georegression.struct.point.Point2D_F64;
import georegression.struct.point.Point3D_F64;
import georegression.struct.se.Se3_F64;
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 TriangulateRefineMetricLS implements RefineTriangulateMetric {
ResidualsTriangulateMetricSimple func = new ResidualsTriangulateMetricSimple();
UnconstrainedLeastSquares minimizer;
double param[] = new double[3];
int maxIterations;
double convergenceTol;
public TriangulateRefineMetricLS(double convergenceTol,
int maxIterations)
{
this.convergenceTol = convergenceTol;
this.maxIterations = maxIterations;
minimizer = FactoryOptimization.levenbergMarquardt(null,false);
}
@Override
public boolean process(List observations, List worldToCamera,
Point3D_F64 worldPt, Point3D_F64 refinedPt)
{
func.setObservations(observations, worldToCamera);
minimizer.setFunction(func,null);
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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