CGAL::Feature_graph::Optimization_parameters_on_surface< NormalEstimator > Class Template Reference

#include <CGAL/Feature_graph/Optimization_parameters.h>

Inherits from

CGAL::Feature_graph::Optimization_parameters< NormalEstimator >.

Definition

template<typename NormalEstimator = Normal_estimator::Normal_estimator_on_surface>
class CGAL::Feature_graph::Optimization_parameters_on_surface< NormalEstimator >

The class Optimization_parameters_on_image describes the parameters for the optimization step with default values adapted for surface inputs.

Template Parameters

Normal_estimator

a model of NormalEstimator.

See also

CGAL::Feature_graph::Optimization_parameters_on_image

CGAL::Feature_graph::Detect_sharp_features_on_labeled_image

CGAL::Feature_graph::Detect_sharp_features_on_surface

Types
typedef Base::Size	Size
	Natural number type.
typedef Base::FT	FT
	Numerical type.

Constructor
template<typename NamedParameters = CGAL::parameters::Default_named_parameters>
	Optimization_parameters_on_surface (const NamedParameters &np=parameters::default_values())
	constructs the parameters used to optimize the feature graph placement on a surface.

Additional Inherited Members
Public Types inherited from CGAL::Feature_graph::Optimization_parameters< NormalEstimator >
typedef std::size_t	Size
	Natural number type.
typedef double	FT
	Numerical type.
typedef NormalEstimator	Normal_estimator
	Type of the functor that evaluates normals.
Public Member Functions inherited from CGAL::Feature_graph::Optimization_parameters< NormalEstimator >
Size	maximum_number_of_iteration () const
	returns the maximum number of iteration of the gradient descent.
FT	start_step_size () const
	returns the step size at the first iteration of the gradient descent.
FT	end_step_size () const
	returns the step size at the last iteration of the gradient descent.
FT	mininmum_energy_delta () const
	returns the minimum energy change to stop the gradient descent iterations.
FT	collapse_distance () const
	returns the distance to collapse adjacent points in a line during the gradient descent.
FT	smoothing_factor () const
	returns the smoothing factor of the energy.
FT	refine_normal_distance () const
	returns the distance to refine the normals of elements near the sharp features.
FT	plane_detection_distance () const
	returns the distance to collect elements near the sharp features to determine the adjacent planes.
Normal_estimator	normal_estimator () const
	returns a functor that estimates the normal on an element.

Constructor & Destructor Documentation

Optimization_parameters_on_surface()

template<typename NormalEstimator = Normal_estimator::Normal_estimator_on_surface>

template<typename NamedParameters = CGAL::parameters::Default_named_parameters>

CGAL::Feature_graph::Optimization_parameters_on_surface< NormalEstimator >::Optimization_parameters_on_surface

(

const NamedParameters &

np = parameters::default_values()

)

constructs the parameters used to optimize the feature graph placement on a surface.

Template Parameters

NamedParameters

a sequence of Named Parameters

Parameters

np	an optional sequence of Named Parameters among the ones listed below.

Optional Named Parameters

maximum_iteration the maximum number of iteration of the gradient descent. Default: Size(20)
start_step_size the step size at the first iteration of the gradient descent. Default: FT(0.0)
end_step_size the step size at the last iteration of the gradient descent. Default: FT(0.0)
min_energy_delta the minimum energy change to stop the gradient descent iterations. Default: FT(1.e-3)
collapse_distance the distance to collapse adjacent points in a line during the gradient descent. Default: FT(0.0)
smoothing_factor the smoothing factor of the energy. 0 means no smoothing, 1 means that the energy will consider smoothing with the same weight as the displacement toward the sharp features of the surface. Default: FT(1.0)
refine_normal_distance the distance to refine the normals of elements near the sharp features. Default: FT(0.0)
plane_detection_distance the distance to collect elements near the sharp features to determine the adjacent planes. Default: FT(0.0)
normal_estimator a functor to evaluate the normals on elements. Default: The CGAL::Feature_graph::Normal_estimator::Normal_estimator_on_surface that will be initialized with the surface.