gtsam::GncOptimizer< GncParameters > Class Template Reference

Public Member Functions
	GncOptimizer (const NonlinearFactorGraph &graph, const Values &initialValues, const GncParameters &params=GncParameters())
	Constructor.
void	setInlierCostThresholds (const double inth)
	Set the maximum weighted residual error for an inlier (same for all factors). More...
void	setInlierCostThresholds (const Vector &inthVec)
	Set the maximum weighted residual error for an inlier (one for each factor). More...
void	setInlierCostThresholdsAtProbability (const double alpha)
	Set the maximum weighted residual error threshold by specifying the probability alpha that the inlier residuals are smaller than that threshold.
void	setWeights (const Vector w)
	Set weights for each factor. More...
const NonlinearFactorGraph &	getFactors () const
	Access a copy of the internal factor graph.
const Values &	getState () const
	Access a copy of the internal values.
const GncParameters &	getParams () const
	Access a copy of the parameters.
const Vector &	getWeights () const
	Access a copy of the GNC weights.
const Vector &	getInlierCostThresholds () const
	Get the inlier threshold.
bool	equals (const GncOptimizer &other, double tol=1e-9) const
	Equals.
Vector	initializeWeightsFromKnownInliersAndOutliers () const
Values	optimize ()
	Compute optimal solution using graduated non-convexity.
double	initializeMu () const
	Initialize the gnc parameter mu such that loss is approximately convex (remark 5 in GNC paper).
double	updateMu (const double mu) const
	Update the gnc parameter mu to gradually increase nonconvexity.
bool	checkMuConvergence (const double mu) const
	Check if we have reached the value of mu for which the surrogate loss matches the original loss.
bool	checkCostConvergence (const double cost, const double prev_cost) const
	Check convergence of relative cost differences.
bool	checkWeightsConvergence (const Vector &weights) const
	Check convergence of weights to binary values.
bool	checkConvergence (const double mu, const Vector &weights, const double cost, const double prev_cost) const
	Check for convergence between consecutive GNC iterations.
NonlinearFactorGraph	makeWeightedGraph (const Vector &weights) const
	Create a graph where each factor is weighted by the gnc weights.
Vector	calculateWeights (const Values &currentEstimate, const double mu)
	Calculate gnc weights.

Public Types
typedef GncParameters::OptimizerType	BaseOptimizer
	For each parameter, specify the corresponding optimizer: e.g., GaussNewtonParams -> GaussNewtonOptimizer.

Member Function Documentation

setInlierCostThresholds() [1/2]

template<class GncParameters >

void gtsam::GncOptimizer< GncParameters >::setInlierCostThresholds ( const double  inth )

inline

Set the maximum weighted residual error for an inlier (same for all factors).

For a factor in the form f(x) = 0.5 * || r(x) ||^2_Omega, the inlier threshold is the largest value of f(x) for the corresponding measurement to be considered an inlier. In other words, an inlier at x is such that 0.5 * || r(x) ||^2_Omega <= barcSq. Assuming an isotropic measurement covariance sigma^2 * Identity, the cost becomes: 0.5 * 1/sigma^2 || r(x) ||^2 <= barcSq. Hence || r(x) ||^2 <= 2 * barcSq * sigma^2.

setInlierCostThresholds() [2/2]

template<class GncParameters >

void gtsam::GncOptimizer< GncParameters >::setInlierCostThresholds ( const Vector &  inthVec )

inline

Set the maximum weighted residual error for an inlier (one for each factor).

For a factor in the form f(x) = 0.5 * || r(x) ||^2_Omega, the inlier threshold is the largest value of f(x) for the corresponding measurement to be considered an inlier. In other words, an inlier at x is such that 0.5 * || r(x) ||^2_Omega <= barcSq.

setWeights()

template<class GncParameters >

void gtsam::GncOptimizer< GncParameters >::setWeights ( const Vector  w )

inline

Set weights for each factor.

This is typically not needed, but provides an extra interface for the user to initialize the weightst

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

• /Users/dellaert/git/github/gtsam/nonlinear/GncOptimizer.h