42 #include <pcl/filters/filter_indices.h>
43 #include <pcl/search/pcl_search.h>
79 template<
typename Po
intT>
90 using Ptr = shared_ptr<StatisticalOutlierRemoval<PointT> >;
91 using ConstPtr = shared_ptr<const StatisticalOutlierRemoval<PointT> >;
132 std_mul_ = stddev_mult;
215 filter_name_ =
"StatisticalOutlierRemoval";
281 #ifdef PCL_NO_PRECOMPILE
282 #include <pcl/filters/impl/statistical_outlier_removal.hpp>
Filter represents the base filter class.
shared_ptr< Filter< PointT > > Ptr
shared_ptr< const Filter< PointT > > ConstPtr
std::string filter_name_
The filter name.
FilterIndices represents the base class for filters that are about binary point removal.
PCLPointCloud2::Ptr PCLPointCloud2Ptr
PCLPointCloud2::ConstPtr PCLPointCloud2ConstPtr
typename PointCloud::Ptr PointCloudPtr
typename PointCloud::ConstPtr PointCloudConstPtr
PointCloud represents the base class in PCL for storing collections of 3D points.
shared_ptr< PointCloud< PointT > > Ptr
shared_ptr< const PointCloud< PointT > > ConstPtr
int getMeanK()
Get the number of points to use for mean distance estimation.
void applyFilter(PCLPointCloud2 &output) override
Abstract filter method for point cloud.
int mean_k_
The number of points to use for mean distance estimation.
void applyFilter(std::vector< int > &indices) override
Abstract filter method for point cloud indices.
KdTreePtr tree_
A pointer to the spatial search object.
double getStddevMulThresh()
Get the standard deviation multiplier threshold as set by the user.
virtual void generateStatistics(double &mean, double &variance, double &stddev, std::vector< float > &distances)
Compute the statistical values used in both applyFilter methods.
StatisticalOutlierRemoval(bool extract_removed_indices=false)
Empty constructor.
double std_mul_
Standard deviations threshold (i.e., points outside of will be marked as outliers).
void setMeanK(int nr_k)
Set the number of points (k) to use for mean distance estimation.
void setStddevMulThresh(double std_mul)
Set the standard deviation multiplier threshold.
StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data.
StatisticalOutlierRemoval(bool extract_removed_indices=false)
Constructor.
typename pcl::search::Search< PointT >::Ptr SearcherPtr
double getStddevMulThresh()
Get the standard deviation multiplier for the distance threshold calculation.
int getMeanK()
Get the number of nearest neighbors to use for mean distance estimation.
void setStddevMulThresh(double stddev_mult)
Set the standard deviation multiplier for the distance threshold calculation.
void setMeanK(int nr_k)
Set the number of nearest neighbors to use for mean distance estimation.
void applyFilter(std::vector< int > &indices) override
Filtered results are indexed by an indices array.
void applyFilterIndices(std::vector< int > &indices)
Filtered results are indexed by an indices array.
shared_ptr< pcl::search::Search< PointT > > Ptr
shared_ptr< ::pcl::PCLPointCloud2 > Ptr
shared_ptr< const ::pcl::PCLPointCloud2 > ConstPtr
A point structure representing Euclidean xyz coordinates, and the RGB color.