Public Member Functions | Protected Member Functions | Protected Attributes

pcl::StatisticalOutlierRemoval< PointT > Class Template Reference
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StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More...

#include <pcl/filters/statistical_outlier_removal.h>

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List of all members.

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.
void setNegative (bool negative)
 Set whether the inliers should be returned (true), or the outliers (false).
bool getNegative ()
 Get the value of the internal negative_ parameter.

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

Detailed Description

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

StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data.

For more information check:

Note:
setFilterFieldName (), setFilterLimits (), and setFilterLimitNegative () are ignored.
Author:
Radu Bogdan Rusu

Definition at line 61 of file statistical_outlier_removal.h.


Constructor & Destructor Documentation

template<typename PointT >
pcl::StatisticalOutlierRemoval< PointT >::StatisticalOutlierRemoval ( bool  extract_removed_indices = false  )  [inline]

Empty constructor.

Definition at line 80 of file statistical_outlier_removal.h.


Member Function Documentation

template<typename PointT >
void pcl::StatisticalOutlierRemoval< PointT >::applyFilter ( PointCloud output  )  [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 97 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 134 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 116 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 90 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 125 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 109 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 141 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 151 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 145 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 148 of file statistical_outlier_removal.h.


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