boofcv.alg.geo.pose

Class PnPJacobianRodrigues

java.lang.Object

boofcv.alg.geo.pose.PnPJacobianRodrigues

All Implemented Interfaces:

FunctionNtoMxN

public class PnPJacobianRodrigues
extends java.lang.Object
implements FunctionNtoMxN

Computes the Jacobian of the error function in PnPResidualReprojection. For a calibrated camera given observations in normalized image coordinates. The rotation matrix is assumed to be parameterized using Rodrigues_F64 coordinates.

Constructor Summary

Constructors

Constructor and Description
PnPJacobianRodrigues()

Method Summary

Modifier and Type	Method and Description
int	getNumOfInputsN() Number of input parameters and columns in output matrix.
int	getNumOfOutputsM() Number of rows in output matrix.
void	process(double[] input, double[] output) Processes the input vector to output a 2D a matrix.
void	setObservations(java.util.List<Point2D3D> observations)

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

PnPJacobianRodrigues

public PnPJacobianRodrigues()

Method Detail

setObservations

public void setObservations(java.util.List<Point2D3D> observations)

getNumOfInputsN

public int getNumOfInputsN()

Description copied from interface: FunctionNtoMxN

Number of input parameters and columns in output matrix. Typically the parameters you are optimizing.

Specified by:

getNumOfInputsN in interface FunctionNtoMxN

Returns:

Number of input parameters

getNumOfOutputsM

public int getNumOfOutputsM()

Description copied from interface: FunctionNtoMxN

Number of rows in output matrix. Typically the functions that are being optimized.

Specified by:

getNumOfOutputsM in interface FunctionNtoMxN

Returns:

Number of rows in output matrix.

process

public void process(double[] input,
                    double[] output)

Description copied from interface: FunctionNtoMxN

Processes the input vector to output a 2D a matrix. The matrix has a dimension of M rows and N columns and is formatted as a row major 1D-array. EJML can be used to provide a matrix wrapper around the output array: DenseMatrix J = DenseMatrix.wrap(m,n,output);

The user can modify the input parameters here and the optimizer must use those changes.

Specified by:

process in interface FunctionNtoMxN

Parameters:

input - Vector with input parameters.

output - Row major array with M rows and N columns.