StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More...

#include <pcl/filters/statistical_outlier_removal.h>

Inheritance diagram for pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >:

Collaboration diagram for pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >:

Public Types
using	Ptr

using	ConstPtr

Public Types inherited from pcl::FilterIndices< pcl::PCLPointCloud2 >
using	PCLPointCloud2 = pcl::PCLPointCloud2

using	PointCloud

using	Ptr

using	ConstPtr

Public Types inherited from pcl::Filter< pcl::PCLPointCloud2 >
using	Ptr = shared_ptr<Filter<pcl::PCLPointCloud2> >

using	ConstPtr = shared_ptr<const Filter<pcl::PCLPointCloud2> >

using	PCLPointCloud2 = pcl::PCLPointCloud2

using	PCLPointCloud2Ptr = PCLPointCloud2::Ptr

using	PCLPointCloud2ConstPtr = PCLPointCloud2::ConstPtr

using	Ptr

using	ConstPtr

using	PointCloud

using	PointCloudPtr

using	PointCloudConstPtr

Public Types inherited from pcl::PCLBase< pcl::PCLPointCloud2 >
using	PCLPointCloud2 = pcl::PCLPointCloud2

using	PCLPointCloud2Ptr = PCLPointCloud2::Ptr

using	PCLPointCloud2ConstPtr = PCLPointCloud2::ConstPtr

using	PointIndicesPtr = PointIndices::Ptr

using	PointIndicesConstPtr = PointIndices::ConstPtr

using	PointCloud

using	PointCloudPtr

using	PointCloudConstPtr

using	PointIndicesPtr

using	PointIndicesConstPtr

Public Member Functions
	StatisticalOutlierRemoval (bool extract_removed_indices=false)
	Empty constructor.

void	setMeanK (int nr_k)
	Set the number of points (k) to use for mean distance estimation.

int	getMeanK ()
	Get the number of points to use for mean distance estimation.

void	setStddevMulThresh (double std_mul)
	Set the standard deviation multiplier threshold.

double	getStddevMulThresh ()
	Get the standard deviation multiplier threshold as set by the user.

	StatisticalOutlierRemoval (bool extract_removed_indices=false)
	Constructor.

void	setMeanK (int nr_k)
	Set the number of nearest neighbors to use for mean distance estimation.

int	getMeanK ()
	Get the number of nearest neighbors to use for mean distance estimation.

void	setStddevMulThresh (double stddev_mult)
	Set the standard deviation multiplier for the distance threshold calculation.

double	getStddevMulThresh ()
	Get the standard deviation multiplier for the distance threshold calculation.

void	setSearchMethod (const SearcherPtr &searcher)
	Provide a pointer to the search object.

Public Member Functions inherited from pcl::FilterIndices< pcl::PCLPointCloud2 >
	FilterIndices (bool extract_removed_indices=false)
	Constructor.

void	filter (Indices &indices)
	Calls the filtering method and returns the filtered point cloud indices.

void	setNegative (bool negative)
	Set whether the regular conditions for points filtering should apply, or the inverted conditions.

bool	getNegative () const
	Get whether the regular conditions for points filtering should apply, or the inverted conditions.

void	setKeepOrganized (bool keep_organized)
	Set whether the filtered points should be kept and set to the value given through setUserFilterValue (default: NaN), or removed from the PointCloud, thus potentially breaking its organized structure.

bool	getKeepOrganized () const
	Get whether the filtered points should be kept and set to the value given through setUserFilterValue (default = NaN), or removed from the PointCloud, thus potentially breaking its organized structure.

void	setUserFilterValue (float value)
	Provide a value that the filtered points should be set to instead of removing them.

	FilterIndices (bool extract_removed_indices=false)
	Constructor.

void	filter (Indices &indices)
	Calls the filtering method and returns the filtered point cloud indices.

void	setNegative (bool negative)
	Set whether the regular conditions for points filtering should apply, or the inverted conditions.

bool	getNegative () const
	Get whether the regular conditions for points filtering should apply, or the inverted conditions.

void	setKeepOrganized (bool keep_organized)
	Set whether the filtered points should be kept and set to the value given through setUserFilterValue (default: NaN), or removed from the PointCloud, thus potentially breaking its organized structure.

bool	getKeepOrganized () const
	Get whether the filtered points should be kept and set to the value given through setUserFilterValue (default = NaN), or removed from the PointCloud, thus potentially breaking its organized structure.

void	setUserFilterValue (float value)
	Provide a value that the filtered points should be set to instead of removing them.

Public Member Functions inherited from pcl::Filter< pcl::PCLPointCloud2 >
	Filter (bool extract_removed_indices=false)
	Empty constructor.

IndicesConstPtr const	getRemovedIndices () const
	Get the point indices being removed.

void	getRemovedIndices (PointIndices &pi)
	Get the point indices being removed.

void	filter (PCLPointCloud2 &output)
	Calls the filtering method and returns the filtered dataset in output.

	Filter (bool extract_removed_indices=false)
	Empty constructor.

IndicesConstPtr const	getRemovedIndices () const
	Get the point indices being removed.

void	getRemovedIndices (PointIndices &pi)
	Get the point indices being removed.

void	filter (PointCloud &output)
	Calls the filtering method and returns the filtered dataset in output.

Public Member Functions inherited from pcl::PCLBase< pcl::PCLPointCloud2 >
	PCLBase ()
	Empty constructor.

virtual	~PCLBase ()=default
	destructor.

void	setInputCloud (const PCLPointCloud2ConstPtr &cloud)
	Provide a pointer to the input dataset.

PCLPointCloud2ConstPtr const	getInputCloud () const
	Get a pointer to the input point cloud dataset.

void	setIndices (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.

void	setIndices (const PointIndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.

IndicesPtr const	getIndices () const
	Get a pointer to the vector of indices used.

	PCLBase ()
	Empty constructor.

	PCLBase (const PCLBase &base)
	Copy constructor.

virtual	~PCLBase ()=default
	Destructor.

virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset.

PointCloudConstPtr const	getInputCloud () const
	Get a pointer to the input point cloud dataset.

virtual void	setIndices (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.

virtual void	setIndices (const IndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.

virtual void	setIndices (const PointIndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.

virtual void	setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols)
	Set the indices for the points laying within an interest region of the point cloud.

IndicesPtr	getIndices ()
	Get a pointer to the vector of indices used.

IndicesConstPtr const	getIndices () const
	Get a pointer to the vector of indices used.

const pcl::PCLPointCloud2 &	operator[] (std::size_t pos) const
	Override PointCloud operator[] to shorten code.

Protected Types
using	PointCloud

using	PointCloudPtr

using	PointCloudConstPtr

using	SearcherPtr

Protected Member Functions
void	applyFilter (Indices &indices) override
	Abstract filter method for point cloud indices.

void	applyFilter (PCLPointCloud2 &output) override
	Abstract filter method for point cloud.

virtual void	generateStatistics (double &mean, double &variance, double &stddev, std::vector< float > &distances)
	Compute the statistical values used in both applyFilter methods.

void	applyFilter (Indices &indices) override
	Filtered results are indexed by an indices array.

void	applyFilterIndices (Indices &indices)
	Filtered results are indexed by an indices array.

Protected Member Functions inherited from pcl::FilterIndices< pcl::PCLPointCloud2 >
void	applyFilter (PointCloud &output) override
	Abstract filter method for point cloud.

Protected Member Functions inherited from pcl::Filter< pcl::PCLPointCloud2 >
const std::string &	getClassName () const
	Get a string representation of the name of this class.

virtual void	applyFilter (PointCloud &output)=0
	Abstract filter method.

const std::string &	getClassName () const
	Get a string representation of the name of this class.

Protected Member Functions inherited from pcl::PCLBase< pcl::PCLPointCloud2 >
bool	initCompute ()

bool	deinitCompute ()

bool	initCompute ()
	This method should get called before starting the actual computation.

bool	deinitCompute ()
	This method should get called after finishing the actual computation.

Protected Attributes
int	mean_k_ {2}
	The number of points to use for mean distance estimation.

double	std_mul_ {0.0}
	Standard deviations threshold (i.e., points outside of $\mu \pm \sigma \cdot std\_mul$ will be marked as outliers).

KdTreePtr	tree_
	A pointer to the spatial search object.

Protected Attributes inherited from pcl::FilterIndices< pcl::PCLPointCloud2 >
bool	negative_ {false}
	False = normal filter behavior (default), true = inverted behavior.

bool	keep_organized_ {false}
	False = remove points (default), true = redefine points, keep structure.

float	user_filter_value_
	The user given value that the filtered point dimensions should be set to (default = NaN).

bool	negative_
	False = normal filter behavior (default), true = inverted behavior.

bool	keep_organized_
	False = remove points (default), true = redefine points, keep structure.

float	user_filter_value_
	The user given value that the filtered point dimensions should be set to (default = NaN).

Protected Attributes inherited from pcl::Filter< pcl::PCLPointCloud2 >
IndicesPtr	removed_indices_
	Indices of the points that are removed.

bool	extract_removed_indices_
	Set to true if we want to return the indices of the removed points.

std::string	filter_name_
	The filter name.

IndicesPtr	removed_indices_
	Indices of the points that are removed.

std::string	filter_name_
	The filter name.

bool	extract_removed_indices_
	Set to true if we want to return the indices of the removed points.

Protected Attributes inherited from pcl::PCLBase< pcl::PCLPointCloud2 >
PCLPointCloud2ConstPtr	input_
	The input point cloud dataset.

IndicesPtr	indices_
	A pointer to the vector of point indices to use.

bool	use_indices_
	Set to true if point indices are used.

bool	fake_indices_
	If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud.

std::vector< uindex_t >	field_sizes_
	The size of each individual field.

index_t	x_idx_
	The x-y-z fields indices.

index_t	y_idx_

index_t	z_idx_

std::string	x_field_name_
	The desired x-y-z field names.

std::string	y_field_name_

std::string	z_field_name_

PointCloudConstPtr	input_
	The input point cloud dataset.

IndicesPtr	indices_
	A pointer to the vector of point indices to use.

bool	use_indices_
	Set to true if point indices are used.

bool	fake_indices_
	If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud.

Detailed Description

StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data.

For more information check:

R. B. Rusu, Z. C. Marton, N. Blodow, M. Dolha, and M. Beetz. Towards 3D Point Cloud Based Object Maps for Household Environments Robotics and Autonomous Systems Journal (Special Issue on Semantic Knowledge), 2008.

Author: Radu Bogdan Rusu

Definition at line 198 of file statistical_outlier_removal.h.

Member Typedef Documentation

◆ ConstPtr

using pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::ConstPtr

Definition at line 92 of file statistical_outlier_removal.h.

◆ PointCloud

using pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::PointCloud

protected

Definition at line 84 of file statistical_outlier_removal.h.

◆ PointCloudConstPtr

using pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::PointCloudConstPtr

protected

Definition at line 86 of file statistical_outlier_removal.h.

◆ PointCloudPtr

using pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::PointCloudPtr

protected

Definition at line 85 of file statistical_outlier_removal.h.

◆ Ptr

using pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::Ptr

Definition at line 91 of file statistical_outlier_removal.h.

◆ SearcherPtr

using pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::SearcherPtr

protected

Definition at line 87 of file statistical_outlier_removal.h.

Constructor & Destructor Documentation

◆ StatisticalOutlierRemoval() [1/2]

pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::StatisticalOutlierRemoval ( bool extract_removed_indices = false )

inline

Empty constructor.

Definition at line 215 of file statistical_outlier_removal.h.

References pcl::Filter< pcl::PCLPointCloud2 >::filter_name_, and pcl::FilterIndices< pcl::PCLPointCloud2 >::FilterIndices().

◆ StatisticalOutlierRemoval() [2/2]

pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::StatisticalOutlierRemoval ( bool extract_removed_indices = false )

inline

Constructor.

Parameters

[in] extract_removed_indices Set to true if you want to be able to extract the indices of points being removed (default = false).

Definition at line 98 of file statistical_outlier_removal.h.

Member Function Documentation

◆ applyFilter() [1/3]

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::applyFilter ( Indices & indices )

inlineoverrideprotectedvirtual

Filtered results are indexed by an indices array.

Parameters

[out] indices The resultant indices.

Implements pcl::FilterIndices< pcl::PCLPointCloud2 >.

Definition at line 165 of file statistical_outlier_removal.h.

◆ applyFilter() [2/3]

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::applyFilter ( Indices & indices )

overrideprotectedvirtual

Abstract filter method for point cloud indices.

Implements pcl::FilterIndices< pcl::PCLPointCloud2 >.

◆ applyFilter() [3/3]

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::applyFilter ( PCLPointCloud2 & output )

overrideprotectedvirtual

Abstract filter method for point cloud.

Implements pcl::FilterIndices< pcl::PCLPointCloud2 >.

◆ applyFilterIndices()

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::applyFilterIndices ( Indices & indices )

protected

Filtered results are indexed by an indices array.

Parameters

[out] indices The resultant indices.

Definition at line 174 of file statistical_outlier_removal.hpp.

◆ generateStatistics()

virtual void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::generateStatistics	(	double &	mean,
		double &	variance,
		double &	stddev,
		std::vector< float > &	distances )

protectedvirtual

Compute the statistical values used in both applyFilter methods.

This method tries to avoid duplicate code.

◆ getMeanK() [1/2]

int pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::getMeanK ( )

inline

Get the number of nearest neighbors to use for mean distance estimation.

Returns: The number of points to use for mean distance estimation.

Definition at line 118 of file statistical_outlier_removal.h.

◆ getMeanK() [2/2]

int pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::getMeanK ( )

inline

Get the number of points to use for mean distance estimation.

Definition at line 232 of file statistical_outlier_removal.h.

References mean_k_.

◆ getStddevMulThresh() [1/2]

double pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::getStddevMulThresh ( )

inline

Get the standard deviation multiplier for the distance threshold calculation.

The distance threshold will be equal to: mean + stddev_mult * stddev. Points will be classified as inlier or outlier if their average neighbor distance is below or above this threshold respectively.

Definition at line 139 of file statistical_outlier_removal.h.

◆ getStddevMulThresh() [2/2]

double pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::getStddevMulThresh ( )

inline

Get the standard deviation multiplier threshold as set by the user.

Definition at line 251 of file statistical_outlier_removal.h.

References std_mul_.

◆ setMeanK() [1/2]

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::setMeanK ( int nr_k )

inline

Set the number of nearest neighbors to use for mean distance estimation.

Parameters

[in] nr_k The number of points to use for mean distance estimation.

Definition at line 109 of file statistical_outlier_removal.h.

◆ setMeanK() [2/2]

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::setMeanK ( int nr_k )

inline

Set the number of points (k) to use for mean distance estimation.

Parameters

nr_k	the number of points to use for mean distance estimation

Definition at line 225 of file statistical_outlier_removal.h.

References mean_k_.

◆ setSearchMethod()

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::setSearchMethod ( const SearcherPtr & searcher )

inline

Provide a pointer to the search object.

Calling this is optional. If not called, the search method will be chosen automatically.

Parameters

[in] searcher a pointer to the spatial search object.

Definition at line 149 of file statistical_outlier_removal.h.

◆ setStddevMulThresh() [1/2]

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::setStddevMulThresh ( double std_mul )

inline

Set the standard deviation multiplier threshold.

All points outside the

$\mu \pm \sigma \cdot std\_mul$

will be considered outliers, where $\mu$ is the estimated mean, and $\sigma$ is the standard deviation.

Parameters

std_mul the standard deviation multiplier threshold

Definition at line 244 of file statistical_outlier_removal.h.

References std_mul_.

◆ setStddevMulThresh() [2/2]

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::setStddevMulThresh ( double stddev_mult )

inline

Set the standard deviation multiplier for the distance threshold calculation.

The distance threshold will be equal to: mean + stddev_mult * stddev. Points will be classified as inlier or outlier if their average neighbor distance is below or above this threshold respectively.

Parameters

[in] stddev_mult The standard deviation multiplier.

Definition at line 129 of file statistical_outlier_removal.h.