pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 > Class Template Reference

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

#include <statistical_outlier_removal.h>

Inheritance diagram for pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >:

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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 ()
	Empty constructor.
Protected Member Functions
void	applyFilter (PointCloud2 &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::KdTree < pcl::PointXYZ >	KdTree
typedef pcl::KdTree < pcl::PointXYZ >::Ptr	KdTreePtr
typedef sensor_msgs::PointCloud2	PointCloud2
typedef PointCloud2::ConstPtr	PointCloud2ConstPtr
typedef PointCloud2::Ptr	PointCloud2Ptr

Detailed Description

template<>
class pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >

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 143 of file statistical_outlier_removal.h.

Member Typedef Documentation

typedef pcl::KdTree<pcl::PointXYZ> pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::KdTree [private]

Definition at line 148 of file statistical_outlier_removal.h.

typedef pcl::KdTree<pcl::PointXYZ>::Ptr pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::KdTreePtr [private]

Definition at line 149 of file statistical_outlier_removal.h.

typedef sensor_msgs::PointCloud2 pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::PointCloud2 [private]

Reimplemented from pcl::Filter< sensor_msgs::PointCloud2 >.

Definition at line 151 of file statistical_outlier_removal.h.

typedef PointCloud2::ConstPtr pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::PointCloud2ConstPtr [private]

Reimplemented from pcl::Filter< sensor_msgs::PointCloud2 >.

Definition at line 153 of file statistical_outlier_removal.h.

typedef PointCloud2::Ptr pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::PointCloud2Ptr [private]

Reimplemented from pcl::Filter< sensor_msgs::PointCloud2 >.

Definition at line 152 of file statistical_outlier_removal.h.

Constructor & Destructor Documentation

pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::StatisticalOutlierRemoval ( ) [inline]

Empty constructor.

Definition at line 157 of file statistical_outlier_removal.h.

Member Function Documentation

void pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::applyFilter ( PointCloud2 & output ) [protected, virtual]

Abstract filter method.

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

Implements pcl::Filter< sensor_msgs::PointCloud2 >.

Definition at line 46 of file statistical_outlier_removal.cpp.

int pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::getMeanK ( ) [inline]

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

Definition at line 168 of file statistical_outlier_removal.h.

bool pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::getNegative ( ) [inline]

Get the value of the internal negative_ parameter. If true, all points _except_ the input indices will be returned.

Definition at line 189 of file statistical_outlier_removal.h.

double pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::getStddevMulThresh ( ) [inline]

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

Definition at line 179 of file statistical_outlier_removal.h.

void pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::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 165 of file statistical_outlier_removal.h.

void pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::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 184 of file statistical_outlier_removal.h.

void pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::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 176 of file statistical_outlier_removal.h.

Member Data Documentation

int pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::mean_k_ [protected]

The number of points to use for mean distance estimation.

Definition at line 193 of file statistical_outlier_removal.h.

bool pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::negative_ [protected]

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

Definition at line 203 of file statistical_outlier_removal.h.

double pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::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 197 of file statistical_outlier_removal.h.

KdTreePtr pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >::tree_ [protected]

A pointer to the spatial search object.

Definition at line 200 of file statistical_outlier_removal.h.

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

pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 > Class Template Reference

Public Member Functions

Protected Member Functions

Protected Attributes

Private Types

Detailed Description

template<> class pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<>
class pcl::StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >