Several point cloud resampling algorithms (octree-based, random, etc.) More...

#include <CloudSamplingTools.h>

Inheritance diagram for CCCoreLib::CloudSamplingTools:

Collaboration diagram for CCCoreLib::CloudSamplingTools:

Classes
struct	SFModulationParams
	Parameters for the scalar-field based modulation of a parameter. More...

Public Types
enum	RESAMPLING_CELL_METHOD { CELL_CENTER , CELL_GRAVITY_CENTER }
	Octree cell resampling methods (see CloudSamplingTools::resampleCloudWithOctree)

enum	SUBSAMPLING_CELL_METHOD { RANDOM_POINT , NEAREST_POINT_TO_CELL_CENTER }
	Octree cell simplifying methods (see CloudSamplingTools::subsampleCloudWithOctree)

Static Public Member Functions
static PointCloud *	resampleCloudWithOctreeAtLevel (GenericIndexedCloudPersist cloud, unsigned char octreeLevel, RESAMPLING_CELL_METHOD resamplingMethod, GenericProgressCallback progressCb=nullptr, DgmOctree *inputOctree=nullptr)
	Resamples a point cloud (process based on the octree) More...

static GenericIndexedCloud *	resampleCloudWithOctree (GenericIndexedCloudPersist cloud, int newNumberOfPoints, RESAMPLING_CELL_METHOD resamplingMethod, GenericProgressCallback progressCb=nullptr, DgmOctree *inputOctree=nullptr)
	Resamples a point cloud (process based on the octree) More...

static ReferenceCloud *	subsampleCloudWithOctreeAtLevel (GenericIndexedCloudPersist cloud, unsigned char octreeLevel, SUBSAMPLING_CELL_METHOD subsamplingMethod, GenericProgressCallback progressCb=nullptr, DgmOctree *inputOctree=nullptr)
	Subsamples a point cloud (process based on the octree) More...

static ReferenceCloud *	subsampleCloudWithOctree (GenericIndexedCloudPersist cloud, int newNumberOfPoints, SUBSAMPLING_CELL_METHOD subsamplingMethod, GenericProgressCallback progressCb=nullptr, DgmOctree *inputOctree=nullptr)
	Subsamples a point cloud (process based on the octree) More...

static ReferenceCloud *	subsampleCloudRandomly (GenericIndexedCloudPersist cloud, unsigned newNumberOfPoints, GenericProgressCallback progressCb=nullptr)
	Subsamples a point cloud (process based on random selections) More...

static ReferenceCloud *	resampleCloudSpatially (GenericIndexedCloudPersist cloud, PointCoordinateType minDistance, const SFModulationParams &modParams, DgmOctree octree=nullptr, GenericProgressCallback *progressCb=nullptr)
	Resamples a point cloud (process based on inter point distance) More...

static ReferenceCloud *	sorFilter (GenericIndexedCloudPersist cloud, int knn=6, double nSigma=1.0, DgmOctree octree=nullptr, GenericProgressCallback *progressCb=nullptr)
	Statistical Outliers Removal (SOR) filter. More...

static ReferenceCloud *	noiseFilter (GenericIndexedCloudPersist cloud, PointCoordinateType kernelRadius, double nSigma, bool removeIsolatedPoints=false, bool useKnn=false, int knn=6, bool useAbsoluteError=true, double absoluteError=0.0, DgmOctree octree=nullptr, GenericProgressCallback *progressCb=nullptr)
	Noise filter based on the distance to the approximate local surface. More...

Static Protected Member Functions
static bool	resampleCellAtLevel (const DgmOctree::octreeCell &cell, void *additionalParameters, NormalizedProgress nProgress=nullptr)
	"Cellular" function to replace one set of points (contained in an octree cell) by a unique point More...

static bool	subsampleCellAtLevel (const DgmOctree::octreeCell &cell, void *additionalParameters, NormalizedProgress nProgress=nullptr)
	"Cellular" function to select a unique point inside an octree cell More...

static bool	applyNoiseFilterAtLevel (const DgmOctree::octreeCell &cell, void *additionalParameters, NormalizedProgress nProgress=nullptr)
	"Cellular" function to apply the noise filter inside an octree cell More...

static bool	applySORFilterAtLevel (const DgmOctree::octreeCell &cell, void *additionalParameters, NormalizedProgress nProgress=nullptr)
	"Cellular" function to apply the SOR filter inside an octree cell More...

Detailed Description

Several point cloud resampling algorithms (octree-based, random, etc.)

Member Function Documentation

◆ applyNoiseFilterAtLevel()

bool CloudSamplingTools::applyNoiseFilterAtLevel	(	const DgmOctree::octreeCell &	cell,
		void **	additionalParameters,
		NormalizedProgress *	nProgress = `nullptr`
	)

staticprotected

"Cellular" function to apply the noise filter inside an octree cell

This function is meant to be applied to all cells of the octree (it is of the form DgmOctree::localFunctionPtr).

Parameters

cell	structure describing the cell on which processing is applied
additionalParameters	see method description
nProgress	optional (normalized) progress notification (per-point)

◆ applySORFilterAtLevel()

bool CloudSamplingTools::applySORFilterAtLevel	(	const DgmOctree::octreeCell &	cell,
		void **	additionalParameters,
		NormalizedProgress *	nProgress = `nullptr`
	)

staticprotected

"Cellular" function to apply the SOR filter inside an octree cell

This function is meant to be applied to all cells of the octree (it is of the form DgmOctree::localFunctionPtr).

Parameters

cell	structure describing the cell on which processing is applied
additionalParameters	see method description
nProgress	optional (normalized) progress notification (per-point)

◆ noiseFilter()

ReferenceCloud * CloudSamplingTools::noiseFilter	(	GenericIndexedCloudPersist *	cloud,
		PointCoordinateType	kernelRadius,
		double	nSigma,
		bool	removeIsolatedPoints = `false`,
		bool	useKnn = `false`,
		int	knn = `6`,
		bool	useAbsoluteError = `true`,
		double	absoluteError = `0.0`,
		DgmOctree *	octree = `nullptr`,
		GenericProgressCallback *	progressCb = `nullptr`
	)

static

Noise filter based on the distance to the approximate local surface.

This filter removes points based on their distance relatively to the best fit plane computed on their neighbors.

Parameters

cloud	the point cloud to resample
kernelRadius	neighborhood radius
nSigma	number of sigmas under which the points should be kept
removeIsolatedPoints	whether to remove isolated points (i.e. with 3 points or less in the neighborhood)
useKnn	whether to use a constant number of neighbors instead of a radius
knn	number of neighbors (if useKnn is true)
useAbsoluteError	whether to use an absolute error instead of 'n' sigmas
absoluteError	absolute error (if useAbsoluteError is true)
octree	associated octree if available
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)

Returns: a reference cloud corresponding to the filtered cloud

◆ resampleCellAtLevel()

bool CloudSamplingTools::resampleCellAtLevel	(	const DgmOctree::octreeCell &	cell,
		void **	additionalParameters,
		NormalizedProgress *	nProgress = `nullptr`
	)

staticprotected

"Cellular" function to replace one set of points (contained in an octree cell) by a unique point

This function is meant to be applied to all cells of the octree (it is of the form DgmOctree::localFunctionPtr). It replaces all points in a cell by a unique one, according to different rules. Method parameters (defined in "additionalParameters") are :

(PointCloud*) point cloud to store new points
(RESAMPLING_CELL_METHOD*) resampling method
Parameters

cell structure describing the cell on which processing is applied

additionalParameters see method description

nProgress optional (normalized) progress notification (per-point)

◆ resampleCloudSpatially()

ReferenceCloud * CloudSamplingTools::resampleCloudSpatially	(	GenericIndexedCloudPersist *	cloud,
		PointCoordinateType	minDistance,
		const SFModulationParams &	modParams,
		DgmOctree *	octree = `nullptr`,
		GenericProgressCallback *	progressCb = `nullptr`
	)

static

Resamples a point cloud (process based on inter point distance)

The cloud is resampled so that there is no point nearer than a given distance to other points It works by picking a reference point, removing all points which are to close to this point, and repeating these two steps until the result is reached

Parameters

cloud	the point cloud to resample
minDistance	the distance under which a point in the resulting cloud cannot have any neighbour
modParams	parameters of the subsampling behavior modulation with a scalar field (optional)
octree	associated octree if available
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)

Returns: a reference cloud corresponding to the resampling 'selection'

◆ resampleCloudWithOctree()

GenericIndexedCloud * CloudSamplingTools::resampleCloudWithOctree	(	GenericIndexedCloudPersist *	cloud,
		int	newNumberOfPoints,
		RESAMPLING_CELL_METHOD	resamplingMethod,
		GenericProgressCallback *	progressCb = `nullptr`,
		DgmOctree *	inputOctree = `nullptr`
	)

static

Resamples a point cloud (process based on the octree)

Same as 'resampleCloudWithOctreeAtLevel' method, apart the fact that instead of giving a specific octree subdivision level as input parameter, one can specify an approximative number of points for the resulting cloud (algorithm will automatically determine the corresponding octree level).

Parameters

cloud	the point cloud to resample
newNumberOfPoints	desired number of points (approximative)
resamplingMethod	resampling method (applied to each octree cell)
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)
inputOctree	if the octree has been already computed, it can be used by the process (avoid recomputation)

Returns: the resampled cloud (new cloud)

◆ resampleCloudWithOctreeAtLevel()

PointCloud * CloudSamplingTools::resampleCloudWithOctreeAtLevel	(	GenericIndexedCloudPersist *	cloud,
		unsigned char	octreeLevel,
		RESAMPLING_CELL_METHOD	resamplingMethod,
		GenericProgressCallback *	progressCb = `nullptr`,
		DgmOctree *	inputOctree = `nullptr`
	)

static

Resamples a point cloud (process based on the octree)

A resampling algorithm is applied inside each cell of the octree. The different resampling methods are represented as an enumerator (see RESAMPLING_CELL_METHOD) and consist in simple processes such as replacing all the points lying in a cell by the cell center or by the points gravity center.

Parameters

cloud	the point cloud to resample
octreeLevel	the octree level at which to perform the resampling process
resamplingMethod	resampling method (applied to each octree cell)
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)
inputOctree	if the octree has been already computed, it can be used by the process (avoid recomputation)

Returns: the resampled cloud (new cloud)

◆ sorFilter()

ReferenceCloud * CloudSamplingTools::sorFilter	(	GenericIndexedCloudPersist *	cloud,
		int	knn = `6`,
		double	nSigma = `1.0`,
		DgmOctree *	octree = `nullptr`,
		GenericProgressCallback *	progressCb = `nullptr`
	)

static

Statistical Outliers Removal (SOR) filter.

This filter removes points based on their mean distance to their distance (by comparing it to the average distance of all points to their neighbors). It is equivalent to PCL StatisticalOutlierRemoval filter (see http://pointclouds.org/documentation/tutorials/statistical_outlier.php)

Parameters

cloud	the point cloud to resample
knn	number of neighbors
nSigma	number of sigmas under which the points should be kept
octree	associated octree if available
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)

Returns: a reference cloud corresponding to the filtered cloud

◆ subsampleCellAtLevel()

bool CloudSamplingTools::subsampleCellAtLevel	(	const DgmOctree::octreeCell &	cell,
		void **	additionalParameters,
		NormalizedProgress *	nProgress = `nullptr`
	)

staticprotected

"Cellular" function to select a unique point inside an octree cell

This function is meant to be applied to all cells of the octree (it is of the form DgmOctree::localFunctionPtr). It chooses one point from the set of points inside a cell, according to different rules. Method parameters (defined in "additionalParameters") are :

(ReferenceCloud*) reference point cloud to store selected points
(SUBSAMPLING_CELL_METHOD*) subampling method
Parameters

cell structure describing the cell on which processing is applied

additionalParameters see method description

nProgress optional (normalized) progress notification (per-point)

◆ subsampleCloudRandomly()

ReferenceCloud * CloudSamplingTools::subsampleCloudRandomly	(	GenericIndexedCloudPersist *	cloud,
		unsigned	newNumberOfPoints,
		GenericProgressCallback *	progressCb = `nullptr`
	)

static

Subsamples a point cloud (process based on random selections)

A very simple subsampling algorithm that simply consists in selecting "n" different points, in a random way.

Parameters

cloud	point cloud to subsample
newNumberOfPoints	desired number of points (exact)
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)

Returns: a reference cloud corresponding to the subsampling 'selection'

◆ subsampleCloudWithOctree()

ReferenceCloud * CloudSamplingTools::subsampleCloudWithOctree	(	GenericIndexedCloudPersist *	cloud,
		int	newNumberOfPoints,
		SUBSAMPLING_CELL_METHOD	subsamplingMethod,
		GenericProgressCallback *	progressCb = `nullptr`,
		DgmOctree *	inputOctree = `nullptr`
	)

static

Subsamples a point cloud (process based on the octree)

Same as 'subsampleCloudWithOctreeAtLevel' method, apart the fact that instead of giving a specific octree subdivision level as input parameter, one can specify an approximative number of points for the resulting cloud (algorithm will automatically determine the corresponding octree level).

Parameters

cloud	point cloud to subsample
newNumberOfPoints	desired number of points (approximative)
subsamplingMethod	resampling method (applied to each octree cell)
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)
inputOctree	if the octree has been already computed, it can be used by the process (avoid recomputation)

Returns: a reference cloud corresponding to the subsampling 'selection'

◆ subsampleCloudWithOctreeAtLevel()

ReferenceCloud * CloudSamplingTools::subsampleCloudWithOctreeAtLevel	(	GenericIndexedCloudPersist *	cloud,
		unsigned char	octreeLevel,
		SUBSAMPLING_CELL_METHOD	subsamplingMethod,
		GenericProgressCallback *	progressCb = `nullptr`,
		DgmOctree *	inputOctree = `nullptr`
	)

static

Subsamples a point cloud (process based on the octree)

A subsampling algorithm is applied inside each cell of the octree. The different subsampling methods are represented as an enumerator (see SUBSAMPLING_CELL_METHOD) and consist in simple processes such as choosing a random point, or the one closest to the cell center.

Parameters

cloud	point cloud to subsample
octreeLevel	octree level at which to perform the subsampling process
subsamplingMethod	subsampling method (applied to each octree cell)
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)
inputOctree	if the octree has been already computed, it can be used by the process (avoid recomputation)

Returns: a reference cloud corresponding to the subsampling 'selection'

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

CloudSamplingTools.h
CloudSamplingTools.cpp

Classes

Public Types

Static Public Member Functions

Static Protected Member Functions

Detailed Description

Member Function Documentation

◆ applyNoiseFilterAtLevel()

◆ applySORFilterAtLevel()

◆ noiseFilter()

◆ resampleCellAtLevel()

◆ resampleCloudSpatially()

◆ resampleCloudWithOctree()

◆ resampleCloudWithOctreeAtLevel()

◆ sorFilter()

◆ subsampleCellAtLevel()

◆ subsampleCloudRandomly()

◆ subsampleCloudWithOctree()

◆ subsampleCloudWithOctreeAtLevel()