CGAL::Poisson_reconstruction_function

转自：http://www.cgal.org/Manual/latest/doc_html/cgal_manual/Surface_reconstruction_points_3_ref/Class_Poisson_reconstruction_function.html#Cross_link_anchor_1498

CGAL::Poisson_reconstruction_function

Definition

Given a set of 3D points with oriented normals sampled on the boundary of a 3D solid, the Poisson Surface Reconstruction method [KBH06] solves for an approximate indicator function of the inferred solid, whose gradient best matches the input normals. The output scalar function, represented in an adaptive octree, is then iso-contoured using an adaptive marching cubes.

Poisson_reconstruction_function implements a variant of this algorithm which solves for a piecewise linear function on a 3D Delaunay triangulation instead of an adaptive octree.

#include

Parameters

template<class Gt>
class Poisson_reconstruction_function;

Parameters

Gt: Geometric traits class.

Is Model for the Concepts

Model of the ImplicitFunction concept.

Types

Poisson_reconstruction_function::Geom_traits
	Geometric traits class.
Poisson_reconstruction_function::FT
	typedef to Geom_traits::FT
Poisson_reconstruction_function::Point
	typedef to Geom_traits::Point_3
Poisson_reconstruction_function::Vector
	typedef to Geom_traits::Vector_3
Poisson_reconstruction_function::Sphere
	typedef to Geom_traits::Sphere_3

Creation

template
Poisson_reconstruction_function fct ( InputIterator first, InputIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap);
	Creates a Poisson implicit function from the [first, beyond) range of points. Template Parameters:  InputIterator: iterator over input points. PointPMap: is a model ofboost::ReadablePropertyMap with a value_type = Point_3. It can be omitted ifInputIterator value_type is convertible to Point_3.NormalPMap: is a model of boost::ReadablePropertyMap with a value_type = Vector_3. Parameters:  first: iterator over the first input point. beyond: past-the-end iterator over the input points.point_pmap: property map to access the position of an input point. normal_pmap: property map to access theoriented normal of an input point.

Operations

Sphere	fct.bounding_sphere () const	Returns a sphere bounding the inferred surface.
template
bool	fct.compute_implicit_function ( SparseLinearAlgebraTraits_d solver =SparseLinearAlgebraTraits_d())
		The function compute_implicit_function() must be called after the insertion of oriented points. It computes the piecewise linear scalar function operator() by: applying Delaunay refinement, solving for operator() at each vertex of the triangulation with a sparse linear solver, and shifting and orienting operator() such that it is 0 at all input points and negative inside the inferred surface. Template parameters:  SparseLinearAlgebraTraits_d: Symmetric definite positive sparse linear solver. IfEigen 3.1 (or greater) is available and CGAL_EIGEN3_ENABLED is defined, the default solver isEigen::ConjugateGradient, otherwise, it is TAUCS Multifrontal Supernodal Cholesky Factorization. Returns:  false if the linear solver fails. Parameters:  solver: sparse linear solver.
FT	fct.operator() ( const Point& p) const
		ImplicitFunction interface: evaluates the implicit function at a given 3D query point. The functioncompute_implicit_function must be called before the first call to operator().
Point	fct.get_inner_point () const	Returns an arbitray point located inside the inferred surface.

Example

See Surface_reconstruction_points_3/poisson_reconstruction_example.cpp.