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BoofCV is an open source Java library for real-time computer vision and robotics applications.

There is a newer version: 1.1.7

/*
 * 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.RefineTriangulateProjective;
import boofcv.alg.geo.triangulate.ResidualsTriangulateProjective;
import georegression.struct.point.Point2D_F64;
import georegression.struct.point.Point4D_F64;
import org.ddogleg.optimization.FactoryOptimization;
import org.ddogleg.optimization.UnconstrainedLeastSquares;
import org.ejml.data.DMatrixRMaj;

import java.util.List;

/**
 * Nonlinear least-squares triangulation for projective geometry in homogenous coordinates.
 *
 * @author Peter Abeles
 */
public class TriangulateRefineProjectiveLS implements RefineTriangulateProjective {

	ResidualsTriangulateProjective func = new ResidualsTriangulateProjective();

	UnconstrainedLeastSquares minimizer;

	double param[] = new double[4];
	int maxIterations;
	double convergenceTol;

	public TriangulateRefineProjectiveLS(double convergenceTol,
										 int maxIterations)
	{
		this.convergenceTol = convergenceTol;
		this.maxIterations = maxIterations;
		minimizer = FactoryOptimization.levenbergMarquardt(null,false);
	}

	@Override
	public boolean process(List observations, List cameraMatrices,
						   Point4D_F64 worldPt, Point4D_F64 refinedPt) {
		func.setObservations(observations, cameraMatrices);
		minimizer.setFunction(func,null);

		param[0] = worldPt.x;
		param[1] = worldPt.y;
		param[2] = worldPt.z;
		param[3] = worldPt.w;

		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];
		refinedPt.w = found[3];

		return true;
	}
}