Optimization Class Reference

Non-linear optimization routines. There are three methods implemented that include Gauss-Newton, Levenberg-Marquardt and Tukey m-estimator. More...

#include <Optimization.h>

Public Types
enum	OptimizeMethod { GAUSSNEWTON , LEVENBERGMARQUARDT , TUKEY_LM }
	Selection between the algorithm used in optimization. Following should be noticed: More...
typedef void(*	EstimateCallback) (cv::Mat &state, cv::Mat &projection, void *param)
	Pointer to the function that projects the state of the system to the measurements. More...

Public Member Functions
	Optimization (int n_params, int n_meas)
	Constructor. More...
cv::Mat	GetErr ()
	Returns the current residual vector. More...
void	CalcJacobian (cv::Mat &x, cv::Mat &J, EstimateCallback Estimate)
	Numerically differentiates and calculates the Jacobian around x. More...
double	Optimize (cv::Mat &parameters, cv::Mat &measurements, double stop, int max_iter, EstimateCallback Estimate, void *param=0, OptimizeMethod method=LEVENBERGMARQUARDT, const cv::Mat &parameters_mask=cv::Mat(), const cv::Mat &J_mat=cv::Mat(), const cv::Mat &weights=cv::Mat())
	Runs the optimization loop with selected parameters. More...

Detailed Description

Non-linear optimization routines. There are three methods implemented that include Gauss-Newton, Levenberg-Marquardt and Tukey m-estimator.

Definition at line 44 of file Optimization.h.

Member Typedef Documentation

EstimateCallback

typedef void(* EstimateCallback) (cv::Mat &state, cv::Mat &projection, void *param)

Pointer to the function that projects the state of the system to the measurements.

Parameters

state	System parameters, e.g. camera parameterization in optical tracking.
projection	The system state projection is stored here. E.g image measurements in optical tracking.
param	Additional parameters to the function. E.g. some constant parameters that are not optimized.

Definition at line 97 of file Optimization.h.

Member Enumeration Documentation

OptimizeMethod

enum OptimizeMethod

Selection between the algorithm used in optimization. Following should be noticed:

• GAUSSNEWTON

Definition at line 71 of file Optimization.h.

Constructor & Destructor Documentation

Optimization()

Optimization	(	int	n_params,
		int	n_meas
	)

Constructor.

Parameters

n_params	Number of parameters to be optimized.
n_meas	Number of measurements that are observed.

Member Function Documentation

CalcJacobian()

void CalcJacobian	(	cv::Mat &	x,
		cv::Mat &	J,
		EstimateCallback	Estimate
	)

Numerically differentiates and calculates the Jacobian around x.

Parameters

x	The set of parameters around which the Jacobian is evaluated.
J	Resulting Jacobian matrix is stored here.
Estimate	The function to be differentiated.

GetErr()

cv::Mat GetErr ( )

inline

Returns the current residual vector.

Returns

Pointer to the residual vector.

Definition at line 86 of file Optimization.h.

Optimize()

double Optimize	(	cv::Mat &	parameters,
		cv::Mat &	measurements,
		double	stop,
		int	max_iter,
		EstimateCallback	Estimate,
		void *	param = 0,
		OptimizeMethod	method = LEVENBERGMARQUARDT,
		const cv::Mat &	parameters_mask = cv::Mat(),
		const cv::Mat &	J_mat = cv::Mat(),
		const cv::Mat &	weights = cv::Mat()
	)

Runs the optimization loop with selected parameters.

Parameters

parameters	Vector of parameters to be optimized. Initial values should be set.
measurements	Vector of measurements that are observed.
stop	Optimization loop ends as the stop limit is reached. Criteria is calculated as
max_iter	Maximum number of iteration loops that are evaluated if stop is not reached.
Estimate	Pointer to the function that maps the state to the measurements. See EstimateCallback.
method	One of the three possible optimization methods.
parameters_mask	Vector that defines the parameters that are optimized. If vector element is 0, corresponding parameter is not altered.
J_mat	Jacobian matrix. If not given, numerical differentation is used.
weights	Weight vector that can be submitted to give different weights to different measurements. Currently works only with OptimizeMethod::TUKEY_LM.

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The documentation for this class was generated from the following file:

• Optimization.h