Point Cloud Library (PCL)  1.7.1
List of all members | Public Member Functions | Protected Member Functions | Protected Attributes
pcl::StatisticalOutlierRemoval< pcl::PCLPointCloud2 > Class Template Reference

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
 

Detailed Description

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

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 202 of file 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 statistical_outlier_removal.h.

Member Function Documentation

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]outputthe resultant filtered point cloud

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

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

Definition at line 237 of file 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 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 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_kthe number of points to use for mean distance estimation

Definition at line 230 of file 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
negativetrue if all points except the input indices will be returned, false otherwise

Definition at line 265 of file 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_multhe standard deviation multiplier threshold

Definition at line 249 of file statistical_outlier_removal.h.

Member Data Documentation

The number of points to use for mean distance estimation.

Definition at line 282 of file statistical_outlier_removal.h.

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

Definition at line 293 of file 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 statistical_outlier_removal.h.

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

A pointer to the spatial search object.

Definition at line 290 of file statistical_outlier_removal.h.


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