Point Cloud Library (PCL)  1.8.1-dev
List of all members | Public Types | Public Member Functions | Protected Types | Protected Member Functions
pcl::StatisticalOutlierRemoval< PointT > 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< PointT >:

Public Types

typedef boost::shared_ptr
< StatisticalOutlierRemoval
< PointT > > 
Ptr
 
typedef boost::shared_ptr
< const
StatisticalOutlierRemoval
< PointT > > 
ConstPtr
 
- Public Types inherited from pcl::FilterIndices< PointT >
typedef pcl::PointCloud< PointTPointCloud
 
typedef boost::shared_ptr
< FilterIndices< PointT > > 
Ptr
 
typedef boost::shared_ptr
< const FilterIndices< PointT > > 
ConstPtr
 
- Public Types inherited from pcl::Filter< PointT >
typedef boost::shared_ptr
< Filter< PointT > > 
Ptr
 
typedef boost::shared_ptr
< const Filter< PointT > > 
ConstPtr
 
typedef pcl::PointCloud< PointTPointCloud
 
typedef PointCloud::Ptr PointCloudPtr
 
typedef PointCloud::ConstPtr PointCloudConstPtr
 
- Public Types inherited from pcl::PCLBase< PointT >
typedef pcl::PointCloud< PointTPointCloud
 
typedef PointCloud::Ptr PointCloudPtr
 
typedef PointCloud::ConstPtr PointCloudConstPtr
 
typedef boost::shared_ptr
< PointIndices
PointIndicesPtr
 
typedef boost::shared_ptr
< PointIndices const > 
PointIndicesConstPtr
 

Public Member Functions

 StatisticalOutlierRemoval (bool extract_removed_indices=false)
 Constructor. More...
 
void setMeanK (int nr_k)
 Set the number of nearest neighbors to use for mean distance estimation. More...
 
int getMeanK ()
 Get the number of nearest neighbors to use for mean distance estimation. More...
 
void setStddevMulThresh (double stddev_mult)
 Set the standard deviation multiplier for the distance threshold calculation. More...
 
double getStddevMulThresh ()
 Get the standard deviation multiplier for the distance threshold calculation. More...
 
- Public Member Functions inherited from pcl::FilterIndices< PointT >
 FilterIndices (bool extract_removed_indices=false)
 Constructor. More...
 
virtual ~FilterIndices ()
 Empty virtual destructor. More...
 
void filter (PointCloud &output)
 
void filter (std::vector< int > &indices)
 Calls the filtering method and returns the filtered point cloud indices. More...
 
void setNegative (bool negative)
 Set whether the regular conditions for points filtering should apply, or the inverted conditions. More...
 
bool getNegative ()
 Get whether the regular conditions for points filtering should apply, or the inverted conditions. More...
 
void setKeepOrganized (bool keep_organized)
 Set whether the filtered points should be kept and set to the value given through setUserFilterValue (default: NaN), or removed from the PointCloud, thus potentially breaking its organized structure. More...
 
bool getKeepOrganized ()
 Get whether the filtered points should be kept and set to the value given through setUserFilterValue (default = NaN), or removed from the PointCloud, thus potentially breaking its organized structure. More...
 
void setUserFilterValue (float value)
 Provide a value that the filtered points should be set to instead of removing them. More...
 
- Public Member Functions inherited from pcl::Filter< PointT >
 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 (PointCloud &output)
 Calls the filtering method and returns the filtered dataset in output. More...
 
- Public Member Functions inherited from pcl::PCLBase< PointT >
 PCLBase ()
 Empty constructor. More...
 
 PCLBase (const PCLBase &base)
 Copy constructor. More...
 
virtual ~PCLBase ()
 Destructor. More...
 
virtual void setInputCloud (const PointCloudConstPtr &cloud)
 Provide a pointer to the input dataset. More...
 
PointCloudConstPtr const getInputCloud () const
 Get a pointer to the input point cloud dataset. More...
 
virtual void setIndices (const IndicesPtr &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
virtual void setIndices (const IndicesConstPtr &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
virtual void setIndices (const PointIndicesConstPtr &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
virtual void setIndices (size_t row_start, size_t col_start, size_t nb_rows, size_t nb_cols)
 Set the indices for the points laying within an interest region of the point cloud. More...
 
IndicesPtr const getIndices ()
 Get a pointer to the vector of indices used. More...
 
IndicesConstPtr const getIndices () const
 Get a pointer to the vector of indices used. More...
 
const PointToperator[] (size_t pos) const
 Override PointCloud operator[] to shorten code. More...
 

Protected Types

typedef FilterIndices< PointT >
::PointCloud 
PointCloud
 
typedef PointCloud::Ptr PointCloudPtr
 
typedef PointCloud::ConstPtr PointCloudConstPtr
 
typedef pcl::search::Search
< PointT >::Ptr 
SearcherPtr
 

Protected Member Functions

void applyFilter (PointCloud &output)
 Filtered results are stored in a separate point cloud. More...
 
void applyFilter (std::vector< int > &indices)
 Filtered results are indexed by an indices array. More...
 
void applyFilterIndices (std::vector< int > &indices)
 Filtered results are indexed by an indices array. More...
 
- Protected Member Functions inherited from pcl::Filter< PointT >
const std::string & getClassName () const
 Get a string representation of the name of this class. More...
 
- Protected Member Functions inherited from pcl::PCLBase< PointT >
bool initCompute ()
 This method should get called before starting the actual computation. More...
 
bool deinitCompute ()
 This method should get called after finishing the actual computation. More...
 

Additional Inherited Members

- Protected Attributes inherited from pcl::FilterIndices< PointT >
bool negative_
 False = normal filter behavior (default), true = inverted behavior. More...
 
bool keep_organized_
 False = remove points (default), true = redefine points, keep structure. More...
 
float user_filter_value_
 The user given value that the filtered point dimensions should be set to (default = NaN). More...
 
- Protected Attributes inherited from pcl::Filter< PointT >
IndicesPtr removed_indices_
 Indices of the points that are removed. More...
 
std::string filter_name_
 The filter name. More...
 
bool extract_removed_indices_
 Set to true if we want to return the indices of the removed points. More...
 
- Protected Attributes inherited from pcl::PCLBase< PointT >
PointCloudConstPtr 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...
 

Detailed Description

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

StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data.

The algorithm iterates through the entire input twice: During the first iteration it will compute the average distance that each point has to its nearest k neighbors. The value of k can be set using setMeanK(). Next, the mean and standard deviation of all these distances are computed in order to determine a distance threshold. The distance threshold will be equal to: mean + stddev_mult * stddev. The multiplier for the standard deviation can be set using setStddevMulThresh(). During the next iteration the points will be classified as inlier or outlier if their average neighbor distance is below or above this threshold respectively.
The neighbors found for each query point will be found amongst ALL points of setInputCloud(), not just those indexed by setIndices(). The setIndices() method only indexes the points that will be iterated through as search query points.

For more information:

Definition at line 81 of file statistical_outlier_removal.h.

Member Typedef Documentation

template<typename PointT>
typedef boost::shared_ptr< const StatisticalOutlierRemoval<PointT> > pcl::StatisticalOutlierRemoval< PointT >::ConstPtr

Definition at line 92 of file statistical_outlier_removal.h.

template<typename PointT>
typedef FilterIndices<PointT>::PointCloud pcl::StatisticalOutlierRemoval< PointT >::PointCloud
protected

Definition at line 84 of file statistical_outlier_removal.h.

template<typename PointT>
typedef PointCloud::ConstPtr pcl::StatisticalOutlierRemoval< PointT >::PointCloudConstPtr
protected

Definition at line 86 of file statistical_outlier_removal.h.

template<typename PointT>
typedef PointCloud::Ptr pcl::StatisticalOutlierRemoval< PointT >::PointCloudPtr
protected

Definition at line 85 of file statistical_outlier_removal.h.

template<typename PointT>
typedef boost::shared_ptr< StatisticalOutlierRemoval<PointT> > pcl::StatisticalOutlierRemoval< PointT >::Ptr

Definition at line 91 of file statistical_outlier_removal.h.

template<typename PointT>
typedef pcl::search::Search<PointT>::Ptr pcl::StatisticalOutlierRemoval< PointT >::SearcherPtr
protected

Definition at line 87 of file statistical_outlier_removal.h.

Constructor & Destructor Documentation

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

Constructor.

Parameters
[in]extract_removed_indicesSet to true if you want to be able to extract the indices of points being removed (default = false).

Definition at line 98 of file statistical_outlier_removal.h.

References pcl::Filter< PointT >::filter_name_.

Member Function Documentation

template<typename PointT >
void pcl::StatisticalOutlierRemoval< PointT >::applyFilter ( PointCloud output)
protectedvirtual

Filtered results are stored in a separate point cloud.

Parameters
[out]outputThe resultant point cloud.

Implements pcl::FilterIndices< PointT >.

Definition at line 48 of file statistical_outlier_removal.hpp.

References pcl::copyPointCloud(), pcl::PointCloud< T >::is_dense, and pcl::PointCloud< T >::points.

template<typename PointT>
void pcl::StatisticalOutlierRemoval< PointT >::applyFilter ( std::vector< int > &  indices)
inlineprotectedvirtual

Filtered results are indexed by an indices array.

Parameters
[out]indicesThe resultant indices.

Implements pcl::FilterIndices< PointT >.

Definition at line 167 of file statistical_outlier_removal.h.

References pcl::StatisticalOutlierRemoval< PointT >::applyFilterIndices().

template<typename PointT >
void pcl::StatisticalOutlierRemoval< PointT >::applyFilterIndices ( std::vector< int > &  indices)
protected

Filtered results are indexed by an indices array.

Parameters
[out]indicesThe resultant indices.

Definition at line 73 of file statistical_outlier_removal.hpp.

Referenced by pcl::StatisticalOutlierRemoval< PointT >::applyFilter().

template<typename PointT>
int pcl::StatisticalOutlierRemoval< PointT >::getMeanK ( )
inline

Get the number of nearest neighbors to use for mean distance estimation.

Returns
The number of points to use for mean distance estimation.

Definition at line 120 of file statistical_outlier_removal.h.

template<typename PointT>
double pcl::StatisticalOutlierRemoval< PointT >::getStddevMulThresh ( )
inline

Get the standard deviation multiplier for the distance threshold calculation.

The distance threshold will be equal to: mean + stddev_mult * stddev. Points will be classified as inlier or outlier if their average neighbor distance is below or above this threshold respectively.

Definition at line 141 of file statistical_outlier_removal.h.

template<typename PointT>
void pcl::StatisticalOutlierRemoval< PointT >::setMeanK ( int  nr_k)
inline

Set the number of nearest neighbors to use for mean distance estimation.

Parameters
[in]nr_kThe number of points to use for mean distance estimation.

Definition at line 111 of file statistical_outlier_removal.h.

template<typename PointT>
void pcl::StatisticalOutlierRemoval< PointT >::setStddevMulThresh ( double  stddev_mult)
inline

Set the standard deviation multiplier for the distance threshold calculation.

The distance threshold will be equal to: mean + stddev_mult * stddev. Points will be classified as inlier or outlier if their average neighbor distance is below or above this threshold respectively.

Parameters
[in]stddev_multThe standard deviation multiplier.

Definition at line 131 of file statistical_outlier_removal.h.


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