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

#include <pcl/filters/statistical_outlier_removal.h>

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

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

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

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

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

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

void	setNegative (bool negative)
	Set whether the indices should be returned, or all points except the indices. More...

bool	getNegative ()
	Get the value of the internal negative_ parameter. More...

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

virtual	~Filter ()
	Empty destructor. More...

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

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

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

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

virtual	~PCLBase ()
	destructor. More...

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

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

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

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

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

Protected Member Functions
void	applyFilter (PCLPointCloud2 &output)
	Abstract filter method. More...

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

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

bool	deinitCompute ()

Protected Attributes
int	mean_k_
	The number of points to use for mean distance estimation. More...

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

KdTreePtr	tree_
	A pointer to the spatial search object. More...

bool	negative_
	If true, the outliers will be returned instead of the inliers (default: false). More...

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

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

std::string	filter_name_
	The filter name. More...

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

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

bool	use_indices_
	Set to true if point indices are used. More...

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

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

int	x_idx_
	The x-y-z fields indices. More...

int	y_idx_

int	z_idx_

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

std::string	y_field_name_

std::string	z_field_name_

Additional Inherited Members
Public Types inherited from pcl::Filter< pcl::PCLPointCloud2 >
typedef boost::shared_ptr< Filter< pcl::PCLPointCloud2 > >	Ptr

typedef boost::shared_ptr< const Filter< pcl::PCLPointCloud2 > >	ConstPtr

typedef pcl::PCLPointCloud2	PCLPointCloud2

typedef PCLPointCloud2::Ptr	PCLPointCloud2Ptr

typedef PCLPointCloud2::ConstPtr	PCLPointCloud2ConstPtr

Public Types inherited from pcl::PCLBase< pcl::PCLPointCloud2 >
typedef pcl::PCLPointCloud2	PCLPointCloud2

typedef boost::shared_ptr< PCLPointCloud2 >	PCLPointCloud2Ptr

typedef boost::shared_ptr< PCLPointCloud2 const >	PCLPointCloud2ConstPtr

typedef boost::shared_ptr< PointIndices >	PointIndicesPtr

typedef boost::shared_ptr< PointIndices const >	PointIndicesConstPtr

Detailed Description

template<>
class pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >

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.

Note: setFilterFieldName (), setFilterLimits (), and setFilterLimitNegative () are ignored.

Author: Radu Bogdan Rusu

Definition at line 201 of file statistical_outlier_removal.h.

Constructor & Destructor Documentation

◆ StatisticalOutlierRemoval()

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

inline

Empty constructor.

Definition at line 218 of file statistical_outlier_removal.h.

References pcl::Filter< PointT >::filter_name_.

Member Function Documentation

◆ applyFilter()

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

protectedvirtual

Abstract filter method.

The implementation needs to set output.{data, row_step, point_step, width, height, is_dense}.

Parameters

[out] output the resultant filtered point cloud

Implements pcl::Filter< pcl::PCLPointCloud2 >.

◆ getMeanK()

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

inline

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

Definition at line 236 of file statistical_outlier_removal.h.

◆ getNegative()

bool pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::getNegative ( )

inline

Get the value of the internal negative_ parameter.

If true, all points except the input indices will be returned.

Returns: The value of the "negative" flag

Definition at line 274 of file statistical_outlier_removal.h.

References pcl::FilterIndices< PointT >::negative_.

◆ getStddevMulThresh()

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

inline

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

Definition at line 255 of file statistical_outlier_removal.h.

◆ setMeanK()

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 229 of file statistical_outlier_removal.h.

◆ setNegative()

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::setNegative ( bool negative )

inline

Set whether the indices should be returned, or all points except the indices.

Parameters

negative true if all points except the input indices will be returned, false otherwise

Definition at line 264 of file statistical_outlier_removal.h.

References pcl::FilterIndices< PointT >::negative_.

◆ setStddevMulThresh()

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 248 of file statistical_outlier_removal.h.

Member Data Documentation

◆ mean_k_

int pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::mean_k_

protected

The number of points to use for mean distance estimation.

Definition at line 281 of file statistical_outlier_removal.h.

◆ negative_

bool pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::negative_

protected

If true, the outliers will be returned instead of the inliers (default: false).

Definition at line 292 of file statistical_outlier_removal.h.

◆ std_mul_

double pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::std_mul_

protected

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

Definition at line 286 of file statistical_outlier_removal.h.

◆ tree_

KdTreePtr pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::tree_

protected

A pointer to the spatial search object.

Definition at line 289 of file statistical_outlier_removal.h.

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

/build/pcl-qv3n_B/pcl-1.8.1+dfsg1/filters/include/pcl/filters/statistical_outlier_removal.h

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

template<> class pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >

Constructor & Destructor Documentation

◆ StatisticalOutlierRemoval()

Member Function Documentation

◆ applyFilter()

◆ getMeanK()

◆ getNegative()

◆ getStddevMulThresh()

◆ setMeanK()

◆ setNegative()

◆ setStddevMulThresh()

Member Data Documentation

◆ mean_k_

◆ negative_

◆ std_mul_

◆ tree_

template<>
class pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >