StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. For more information check: More...

#include <statistical_outlier_removal.h>

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

[legend]

List of all members.

Public Member Functions
int	getMeanK ()
	Get the number of points to use for mean distance estimation.
bool	getNegative ()
	Get the value of the internal negative_ parameter. If true, all points except the input indices will be returned.
double	getStddevMulThresh ()
	Get the standard deviation multiplier threshold as set by the user.
void	setMeanK (int nr_k)
	Set the number of points (k) to use for mean distance estimation.
void	setNegative (bool negative)
	Set whether the indices should be returned, or all points except the indices.
void	setStddevMulThresh (double std_mul)
	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.
	StatisticalOutlierRemoval (bool extract_removed_indices=false)
	Empty constructor.
Protected Member Functions
void	applyFilter (PCLPointCloud2 &output)
	Abstract filter method.
Protected Attributes
int	mean_k_
	The number of points to use for mean distance estimation.
bool	negative_
	If true, the outliers will be returned instead of the inliers (default: false).
double	std_mul_
	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.
Private Types
typedef pcl::search::Search < pcl::PointXYZ >	KdTree
typedef pcl::search::Search < pcl::PointXYZ >::Ptr	KdTreePtr
typedef pcl::PCLPointCloud2	PCLPointCloud2
typedef PCLPointCloud2::ConstPtr	PCLPointCloud2ConstPtr
typedef PCLPointCloud2::Ptr	PCLPointCloud2Ptr

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 202 of file filters/include/pcl/filters/statistical_outlier_removal.h.

Member Typedef Documentation

typedef pcl::search::Search<pcl::PointXYZ> pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::KdTree [private]

Definition at line 210 of file filters/include/pcl/filters/statistical_outlier_removal.h.

typedef pcl::search::Search<pcl::PointXYZ>::Ptr pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::KdTreePtr [private]

Definition at line 211 of file filters/include/pcl/filters/statistical_outlier_removal.h.

typedef pcl::PCLPointCloud2 pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::PCLPointCloud2 [private]

Reimplemented from pcl::Filter< pcl::PCLPointCloud2 >.

Definition at line 213 of file filters/include/pcl/filters/statistical_outlier_removal.h.

typedef PCLPointCloud2::ConstPtr pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::PCLPointCloud2ConstPtr [private]

Reimplemented from pcl::Filter< pcl::PCLPointCloud2 >.

Definition at line 215 of file filters/include/pcl/filters/statistical_outlier_removal.h.

typedef PCLPointCloud2::Ptr pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::PCLPointCloud2Ptr [private]

Reimplemented from pcl::Filter< pcl::PCLPointCloud2 >.

Definition at line 214 of file filters/include/pcl/filters/statistical_outlier_removal.h.

Constructor & Destructor Documentation

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

Empty constructor.

Definition at line 219 of file filters/include/pcl/filters/statistical_outlier_removal.h.

Member Function Documentation

void pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::applyFilter ( PCLPointCloud2 & output ) [protected, virtual]

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 >.

Definition at line 46 of file filters/src/statistical_outlier_removal.cpp.

int pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::getMeanK ( ) [inline]

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

Definition at line 237 of file filters/include/pcl/filters/statistical_outlier_removal.h.

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 275 of file filters/include/pcl/filters/statistical_outlier_removal.h.

double pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::getStddevMulThresh ( ) [inline]

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

Definition at line 256 of file filters/include/pcl/filters/statistical_outlier_removal.h.

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 230 of file filters/include/pcl/filters/statistical_outlier_removal.h.

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 265 of file filters/include/pcl/filters/statistical_outlier_removal.h.

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 249 of file filters/include/pcl/filters/statistical_outlier_removal.h.

Member Data Documentation

int pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::mean_k_ [protected]

The number of points to use for mean distance estimation.

Definition at line 282 of file filters/include/pcl/filters/statistical_outlier_removal.h.

bool pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::negative_ [protected]

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

Definition at line 293 of file filters/include/pcl/filters/statistical_outlier_removal.h.

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 287 of file filters/include/pcl/filters/statistical_outlier_removal.h.

KdTreePtr pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 >::tree_ [protected]

A pointer to the spatial search object.

Definition at line 290 of file filters/include/pcl/filters/statistical_outlier_removal.h.

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

Public Member Functions

Protected Member Functions

Protected Attributes

Private Types

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

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