pcl::StatisticalOutlierRemoval< PointT > 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< PointT >:

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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 inliers should be returned (true), or the outliers (false).
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 (PointCloud &output)
	Apply the filter.
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< PointT >	KdTree
typedef pcl::KdTree< PointT >::Ptr	KdTreePtr
typedef Filter< PointT > ::PointCloud	PointCloud
typedef PointCloud::ConstPtr	PointCloudConstPtr
typedef PointCloud::Ptr	PointCloudPtr

Detailed Description

template<typename PointT>
class pcl::StatisticalOutlierRemoval< PointT >

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 61 of file statistical_outlier_removal.h.

Member Typedef Documentation

template<typename PointT>

typedef pcl::KdTree<PointT> pcl::StatisticalOutlierRemoval< PointT >::KdTree [private]

Definition at line 68 of file statistical_outlier_removal.h.

template<typename PointT>

typedef pcl::KdTree<PointT>::Ptr pcl::StatisticalOutlierRemoval< PointT >::KdTreePtr [private]

Definition at line 69 of file statistical_outlier_removal.h.

template<typename PointT>

typedef Filter<PointT>::PointCloud pcl::StatisticalOutlierRemoval< PointT >::PointCloud [private]

Reimplemented from pcl::Filter< PointT >.

Definition at line 71 of file statistical_outlier_removal.h.

template<typename PointT>

typedef PointCloud::ConstPtr pcl::StatisticalOutlierRemoval< PointT >::PointCloudConstPtr [private]

Reimplemented from pcl::Filter< PointT >.

Definition at line 73 of file statistical_outlier_removal.h.

template<typename PointT>

typedef PointCloud::Ptr pcl::StatisticalOutlierRemoval< PointT >::PointCloudPtr [private]

Reimplemented from pcl::Filter< PointT >.

Definition at line 72 of file statistical_outlier_removal.h.

Constructor & Destructor Documentation

template<typename PointT>

pcl::StatisticalOutlierRemoval< PointT >::StatisticalOutlierRemoval ( ) [inline]

Empty constructor.

Definition at line 77 of file statistical_outlier_removal.h.

Member Function Documentation

template<typename PointT >

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

Apply the filter.

Parameters:

output

the resultant point cloud message

Implements pcl::Filter< PointT >.

Definition at line 45 of file statistical_outlier_removal.hpp.

template<typename PointT>

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

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

Definition at line 88 of file statistical_outlier_removal.h.

template<typename PointT>

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

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

Definition at line 109 of file statistical_outlier_removal.h.

template<typename PointT>

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

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

Definition at line 99 of file statistical_outlier_removal.h.

template<typename PointT>

void pcl::StatisticalOutlierRemoval< PointT >::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 85 of file statistical_outlier_removal.h.

template<typename PointT>

void pcl::StatisticalOutlierRemoval< PointT >::setNegative ( bool negative ) [inline]

Set whether the inliers should be returned (true), or the outliers (false).

Parameters:

negative

true if the inliers should be returned, false otherwise

Definition at line 104 of file statistical_outlier_removal.h.

template<typename PointT>

void pcl::StatisticalOutlierRemoval< PointT >::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 96 of file statistical_outlier_removal.h.

Member Data Documentation

template<typename PointT>

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

The number of points to use for mean distance estimation.

Definition at line 113 of file statistical_outlier_removal.h.

template<typename PointT>

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

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

Definition at line 123 of file statistical_outlier_removal.h.

template<typename PointT>

double pcl::StatisticalOutlierRemoval< PointT >::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 117 of file statistical_outlier_removal.h.

template<typename PointT>

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

A pointer to the spatial search object.

Definition at line 120 of file statistical_outlier_removal.h.

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

pcl::StatisticalOutlierRemoval< PointT > Class Template Reference

Public Member Functions

Protected Member Functions

Protected Attributes

Private Types

Detailed Description

template<typename PointT> class pcl::StatisticalOutlierRemoval< PointT >

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<typename PointT>
class pcl::StatisticalOutlierRemoval< PointT >