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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.pose;
import boofcv.abst.geo.RefinePnP;
import boofcv.abst.geo.optimization.ResidualsCodecToMatrix;
import boofcv.alg.geo.pose.PnPJacobianRodrigues;
import boofcv.alg.geo.pose.PnPResidualReprojection;
import boofcv.alg.geo.pose.PnPRodriguesCodec;
import boofcv.struct.geo.Point2D3D;
import georegression.struct.se.Se3_F64;
import org.ddogleg.fitting.modelset.ModelCodec;
import org.ddogleg.optimization.FactoryOptimization;
import org.ddogleg.optimization.UnconstrainedLeastSquares;
import java.util.List;
/**
* Minimizes the projection residual error in a calibrated camera for a pose estimate.
* Rotation is encoded using rodrigues coordinates.
*
* @author Peter Abeles
*/
public class PnPRefineRodrigues implements RefinePnP {
ModelCodec paramModel = new PnPRodriguesCodec();
ResidualsCodecToMatrix func;
PnPJacobianRodrigues jacobian = new PnPJacobianRodrigues();
double param[];
UnconstrainedLeastSquares minimizer;
int maxIterations;
double convergenceTol;
public PnPRefineRodrigues(double convergenceTol, int maxIterations )
{
this.maxIterations = maxIterations;
this.convergenceTol = convergenceTol;
this.minimizer = FactoryOptimization.levenbergMarquardt(null,false);
func = new ResidualsCodecToMatrix<>(paramModel, new PnPResidualReprojection(), new Se3_F64());
param = new double[paramModel.getParamLength()];
}
@Override
public boolean fitModel(List obs, Se3_F64 worldToCamera, Se3_F64 refinedWorldToCamera) {
paramModel.encode(worldToCamera, param);
func.setObservations(obs);
jacobian.setObservations(obs);
minimizer.setFunction(func,jacobian);
minimizer.initialize(param,0,convergenceTol*obs.size());
boolean updated = false;
for( int i = 0; i < maxIterations; i++ ) {
boolean converged = minimizer.iterate();
if( converged || minimizer.isUpdated() ) {
// save the results
paramModel.decode(minimizer.getParameters(), refinedWorldToCamera);
updated = true;
}
if( converged ) {
if( i == 0 ) {
// if it converted on the first iteration then that means it already
// meet convergence. use input to avoid introduction of small numerical errors
refinedWorldToCamera.set(worldToCamera);
}
break;
}
}
return updated;
}
@Override
public double getFitScore() {
return minimizer.getFunctionValue();
}
}
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