A point cloud manager class that uses the STANN nearest neighbor search library to handle the data. This class calculates robust surface normals for the given point set as described in the SSRR2010 paper. More...

#include <AdaptiveKSearchSurface.hpp>

Inheritance diagram for lvr2::AdaptiveKSearchSurface< BaseVecT >:

[legend]

Public Member Functions
	AdaptiveKSearchSurface (PointBufferPtr loader, std::string searchTreeName, int kn=10, int ki=10, int kd=10, int calcMethod=0, string poseFile="")
	Constructor. More...

	AdaptiveKSearchSurface ()
	standard Constructor More...

virtual void	calculateSurfaceNormals ()
	Calculates initial point normals using a least squares fit to the m_kn nearest points. More...

virtual pair< typename BaseVecT::CoordType, typename BaseVecT::CoordType >	distance (BaseVecT v) const
	See interface documentation. More...

void	interpolateSurfaceNormals ()
	Returns the number of managed points. More...

virtual	~AdaptiveKSearchSurface ()
	Destructor. More...

Public Member Functions inherited from lvr2::PointsetSurface< BaseVecT >
const BoundingBox< BaseVecT > &	getBoundingBox () const
	Returns the bounding box of the point set. More...

virtual Normal< float >	getInterpolatedNormal (const BaseVecT &position) const
	Interpolates a surface normal at the given position. More...

virtual PointBufferPtr	pointBuffer () const
	Returns the internal point buffer. After a call of calculateSurfaceNormals the buffer will contain normal information. More...

std::shared_ptr< SearchTree< BaseVecT > >	searchTree () const
	Returns a pointer to the search tree. More...

void	setKd (int k)
	Sets the number of points that is used for distance evaluation, i.e. an average of the distance to the k nearest data points is given (useful in noisy data sets). More...

void	setKi (int k)
	If k is > 0, each normal will be averaged with its k neighbors. More...

void	setKn (int k)
	Sets the size of the k-neighborhood that is used for normal estimation. More...

Private Member Functions
bool	boundingBoxOK (float dx, float dy, float dz)
	Checks if the bounding box of a point set is "well formed", i.e. no dimension is significantly larger than the other. More...

Plane< BaseVecT >	calcPlane (const BaseVecT &queryPoint, int k, const vector< size_t > &id)
	Returns the mean distance of the given point set from the given plane. More...

Plane< BaseVecT >	calcPlaneIterative (const BaseVecT &queryPoint, int k, const vector< size_t > &id)

Plane< BaseVecT >	calcPlaneRANSAC (const BaseVecT &queryPoint, int k, const vector< size_t > &id, bool &ok)

void	init ()
	Returns the k closest neighbor vertices to a given queryy point. More...

void	parseScanPoses (string posefile)
	Parses the file with scan poses and creates a search tree to search for the nearest pose when flipping normals. More...

Private Attributes
int	m_calcMethod

BaseVecT	m_centroid
	The centroid of the point set. More...

std::shared_ptr< SearchTree< BaseVecT > >	m_poseTree
	Search tree for scan poses. More...

string	m_searchTreeName
	Type of used search tree. More...

Additional Inherited Members
Protected Member Functions inherited from lvr2::PointsetSurface< BaseVecT >
	PointsetSurface (PointBufferPtr pointcloud)
	Constructor. Stores the given buffer pointer. If the point buffer does not contain surface normals, you will have to call calculateSurfaceNormals before the first call . More...

	PointsetSurface ()

Protected Attributes inherited from lvr2::PointsetSurface< BaseVecT >
BoundingBox< BaseVecT >	m_boundingBox
	The bounding box of the point cloud. More...

int	m_kd
	The number of points used for distance function evaluation. More...

int	m_ki
	The number of points used for normal interpolation. More...

int	m_kn
	The number of points used for normal estimation. More...

PointBufferPtr	m_pointBuffer
	The point cloud used for surface approximation. More...

std::shared_ptr< SearchTree< BaseVecT > >	m_searchTree
	The search tree that is built from the point cloud data. More...

Detailed Description

template<typename BaseVecT>
class lvr2::AdaptiveKSearchSurface< BaseVecT >

A point cloud manager class that uses the STANN nearest neighbor search library to handle the data. This class calculates robust surface normals for the given point set as described in the SSRR2010 paper.

Definition at line 98 of file AdaptiveKSearchSurface.hpp.

Constructor & Destructor Documentation

◆ AdaptiveKSearchSurface() [1/2]

template<typename BaseVecT>

lvr2::AdaptiveKSearchSurface< BaseVecT >::AdaptiveKSearchSurface	(	PointBufferPtr	loader,
		std::string	searchTreeName,
		int	kn = `10`,
		int	ki = `10`,
		int	kd = `10`,
		int	calcMethod = `0`,
		string	poseFile = `""`
	)

Constructor.

Parameters

The	file to read from
searchTN	The of the searchTree type that shall be used
kn	The number of neighbor points used for normal estimation
ki	The number of neighbor points used for normal interpolation
kd	The number of neighbor points used for distance value calculation
calcMethod	Normal calculation method. 0: PCA(default), 1: RANSAC, 2: Iterative

◆ AdaptiveKSearchSurface() [2/2]

template<typename BaseVecT>

lvr2::AdaptiveKSearchSurface< BaseVecT >::AdaptiveKSearchSurface ( )

standard Constructor

m_useRANSAC = true; m_ki = 10; m_kn = 10; m_kd = 10;

This Constructor can be used, if only the method "calcPlaneRANSACfromPoints" is required

◆ ~AdaptiveKSearchSurface()

template<typename BaseVecT>

virtual lvr2::AdaptiveKSearchSurface< BaseVecT >::~AdaptiveKSearchSurface ( )

inlinevirtual

Destructor.

Definition at line 140 of file AdaptiveKSearchSurface.hpp.

Member Function Documentation

◆ boundingBoxOK()

template<typename BaseVecT>

bool lvr2::AdaptiveKSearchSurface< BaseVecT >::boundingBoxOK	(	float	dx,
		float	dy,
		float	dz
	)

private

Checks if the bounding box of a point set is "well formed", i.e. no dimension is significantly larger than the other.

This method is needed to achieve a better quality of the initial normal estimation in sparse scans. Details are described in the SRR2010 paper.

Parameters

dx,dy,dz The side lengths of the bounding box

Returns: true if the given box has valid dimensions.

◆ calcPlane()

template<typename BaseVecT>

Plane<BaseVecT> lvr2::AdaptiveKSearchSurface< BaseVecT >::calcPlane	(	const BaseVecT &	queryPoint,
		int	k,
		const vector< size_t > &	id
	)

private

Returns the mean distance of the given point set from the given plane.

Parameters

p	The query plane
id	A list of point id's
k	The number of points in the list Returns a vertex representation of the given point in the point array
i	A id of a point in the current point set

Returns: A vertex representation of the given point Returns the distance between vertex v and plane p Calculates a tangent plane for the query point using the provided k-neighborhood

Parameters

queryPoint	The point for which the tangent plane is created
k	The size of the used k-neighborhood
id	The positions of the neighborhood points in m_points
ok	True, if RANSAC interpolation was succesfull

◆ calcPlaneIterative()

template<typename BaseVecT>

Plane<BaseVecT> lvr2::AdaptiveKSearchSurface< BaseVecT >::calcPlaneIterative	(	const BaseVecT &	queryPoint,
		int	k,
		const vector< size_t > &	id
	)

private

◆ calcPlaneRANSAC()

template<typename BaseVecT>

Plane<BaseVecT> lvr2::AdaptiveKSearchSurface< BaseVecT >::calcPlaneRANSAC	(	const BaseVecT &	queryPoint,
		int	k,
		const vector< size_t > &	id,
		bool &	ok
	)

private

◆ calculateSurfaceNormals()

template<typename BaseVecT>

virtual void lvr2::AdaptiveKSearchSurface< BaseVecT >::calculateSurfaceNormals ( )

virtual

Calculates initial point normals using a least squares fit to the m_kn nearest points.

Implements lvr2::PointsetSurface< BaseVecT >.

◆ distance()

template<typename BaseVecT>

virtual pair<typename BaseVecT::CoordType, typename BaseVecT::CoordType> lvr2::AdaptiveKSearchSurface< BaseVecT >::distance ( BaseVecT v ) const

virtual

See interface documentation.

Implements lvr2::PointsetSurface< BaseVecT >.

◆ init()

template<typename BaseVecT>

void lvr2::AdaptiveKSearchSurface< BaseVecT >::init ( )

private

Returns the k closest neighbor vertices to a given queryy point.

Parameters

v	A query vertex
k	The (max) number of returned closest points to v
nb	A vector containing the determined closest points Helper function for constructors

◆ interpolateSurfaceNormals()

template<typename BaseVecT>

void lvr2::AdaptiveKSearchSurface< BaseVecT >::interpolateSurfaceNormals ( )

Returns the number of managed points.

Calculates a tangent plane for the query point using the provided k-neighborhood

Parameters

queryPoint	The point for which the tangent plane is created
k	The size of the used k-neighborhood
points	The neighborhood points
ok	True, if RANSAC interpolation was succesfull

Returns: the resulting plane Returns the point at the given index}. If set to true, normals will be calculated using RANSAC instead of plane fitting Interpolate the initial normals with the m_ki neighbors

◆ parseScanPoses()

template<typename BaseVecT>

void lvr2::AdaptiveKSearchSurface< BaseVecT >::parseScanPoses ( string posefile )

private

Parses the file with scan poses and creates a search tree to search for the nearest pose when flipping normals.

Member Data Documentation

◆ m_calcMethod

template<typename BaseVecT>

int lvr2::AdaptiveKSearchSurface< BaseVecT >::m_calcMethod

private

Definition at line 308 of file AdaptiveKSearchSurface.hpp.

◆ m_centroid

template<typename BaseVecT>

BaseVecT lvr2::AdaptiveKSearchSurface< BaseVecT >::m_centroid

private

The centroid of the point set.

Definition at line 303 of file AdaptiveKSearchSurface.hpp.

◆ m_poseTree

template<typename BaseVecT>

std::shared_ptr<SearchTree<BaseVecT> > lvr2::AdaptiveKSearchSurface< BaseVecT >::m_poseTree

private

Search tree for scan poses.

Definition at line 322 of file AdaptiveKSearchSurface.hpp.

◆ m_searchTreeName

template<typename BaseVecT>

string lvr2::AdaptiveKSearchSurface< BaseVecT >::m_searchTreeName

private

Type of used search tree.

Definition at line 325 of file AdaptiveKSearchSurface.hpp.

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

AdaptiveKSearchSurface.hpp

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

template<typename BaseVecT> class lvr2::AdaptiveKSearchSurface< BaseVecT >

Constructor & Destructor Documentation

◆ AdaptiveKSearchSurface() [1/2]

◆ AdaptiveKSearchSurface() [2/2]

◆ ~AdaptiveKSearchSurface()

Member Function Documentation

◆ boundingBoxOK()

◆ calcPlane()

◆ calcPlaneIterative()

◆ calcPlaneRANSAC()

◆ calculateSurfaceNormals()

◆ distance()

◆ init()

◆ interpolateSurfaceNormals()

◆ parseScanPoses()

Member Data Documentation

◆ m_calcMethod

◆ m_centroid

◆ m_poseTree

◆ m_searchTreeName

template<typename BaseVecT>
class lvr2::AdaptiveKSearchSurface< BaseVecT >