Reen::PoissonReconstruction Class Reference

#include <SurfaceTriangulation.h>

Public Member Functions

void perform (const std::vector< Base::Vector3f > &normals)
 Pass the normals to the points given in the constructor. More...
 
void perform (int ksearch=5)
 Set the number of k nearest neighbors to use for the normal estimation. More...
 
 PoissonReconstruction (const Points::PointKernel &, Mesh::MeshObject &)
 
void setDepth (int depth)
 Set the maximum depth of the tree that will be used for surface reconstruction. More...
 
void setSamplesPerNode (float samplesPerNode)
 Set the minimum number of sample points that should fall within an octree node as the octree construction is adapted to sampling density. More...
 
void setSolverDivide (int solverDivide)
 Set the depth at which a block Gauss-Seidel solver is used to solve the Laplacian equation. More...
 

Constructor & Destructor Documentation

◆ PoissonReconstruction()

Reen::PoissonReconstruction::PoissonReconstruction ( const Points::PointKernel ,
Mesh::MeshObject  
)

Member Function Documentation

◆ perform() [1/2]

void Reen::PoissonReconstruction::perform ( const std::vector< Base::Vector3f > &  normals)

Pass the normals to the points given in the constructor.

Parameters
[in]normalsthe normals to the given points.

◆ perform() [2/2]

void Reen::PoissonReconstruction::perform ( int  ksearch = 5)

Set the number of k nearest neighbors to use for the normal estimation.

Parameters
[in]kthe number of k-nearest neighbors

◆ setDepth()

void Reen::PoissonReconstruction::setDepth ( int  depth)

Set the maximum depth of the tree that will be used for surface reconstruction.

Note
Running at depth d corresponds to solving on a voxel grid whose resolution is no larger than 2^d x 2^d x 2^d. Note that since the reconstructor adapts the octree to the sampling density, the specified reconstruction depth is only an upper bound.
Parameters
[in]depththe depth parameter

◆ setSamplesPerNode()

void Reen::PoissonReconstruction::setSamplesPerNode ( float  samplesPerNode)

Set the minimum number of sample points that should fall within an octree node as the octree construction is adapted to sampling density.

Note
For noise-free samples, small values in the range [1.0 - 5.0] can be used. For more noisy samples, larger values in the range [15.0 - 20.0] may be needed to provide a smoother, noise-reduced, reconstruction.
Parameters
[in]samples_per_nodethe given parameter value

◆ setSolverDivide()

void Reen::PoissonReconstruction::setSolverDivide ( int  solverDivide)

Set the depth at which a block Gauss-Seidel solver is used to solve the Laplacian equation.

Note
Using this parameter helps reduce the memory overhead at the cost of a small increase in reconstruction time. (In practice, we have found that for reconstructions of depth 9 or higher a subdivide depth of 7 or 8 can greatly reduce the memory usage.)
Parameters
[in]solver_dividethe given parameter value

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