public LeastSquaresTriangulateCalibrated( double convergenceTol, int maxIterations) { this.convergenceTol = convergenceTol; this.maxIterations = maxIterations; minimizer = FactoryOptimization.leastSquareLevenberg(1e-3); }
public LeastSquaresTriangulateEpipolar(double convergenceTol, int maxIterations) { this.maxIterations = maxIterations; this.convergenceTol = convergenceTol; minimizer = FactoryOptimization.leastSquareLevenberg( 1e-3); }
public LeastSquaresHomography(double convergenceTol, int maxIterations, ModelObservationResidualN residuals ) { this.maxIterations = maxIterations; this.convergenceTol = convergenceTol; this.func = new ResidualsEpipolarMatrixN(null,residuals); minimizer = FactoryOptimization.leastSquareLevenberg( 1e-3); }
public LeastSquaresFundamental(ModelCodec<DenseMatrix64F> paramModel, double convergenceTol, int maxIterations, boolean useSampson) { this.paramModel = paramModel; this.maxIterations = maxIterations; this.convergenceTol = convergenceTol; param = new double[paramModel.getParamLength()]; ModelObservationResidual<DenseMatrix64F,AssociatedPair> residual; if( useSampson ) residual = new FundamentalResidualSampson(); else residual = new FundamentalResidualSimple(); func = new ResidualsEpipolarMatrix(paramModel,residual); minimizer = FactoryOptimization.leastSquareLevenberg(1e-3); }
public PnPRefineRodrigues(double convergenceTol, int maxIterations ) { this.maxIterations = maxIterations; this.convergenceTol = convergenceTol; this.minimizer = FactoryOptimization.leastSquareLevenberg(1e-3); func = new ResidualsCodecToMatrix<>(paramModel, new PnPResidualReprojection(), new Se3_F64()); param = new double[paramModel.getParamLength()]; }