Point Cloud Library (PCL)
1.9.1
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40 #ifndef PCL_FILTERS_STATISTICAL_OUTLIER_REMOVAL_H_
41 #define PCL_FILTERS_STATISTICAL_OUTLIER_REMOVAL_H_
43 #include <pcl/filters/filter_indices.h>
44 #include <pcl/search/pcl_search.h>
80 template<
typename Po
intT>
91 typedef boost::shared_ptr< StatisticalOutlierRemoval<PointT> >
Ptr;
92 typedef boost::shared_ptr< const StatisticalOutlierRemoval<PointT> >
ConstPtr;
133 std_mul_ = stddev_mult;
220 std_mul_ (0.0), tree_ ()
222 filter_name_ =
"StatisticalOutlierRemoval";
273 applyFilter (std::vector<int> &indices);
284 generateStatistics (
double& mean,
double& variance,
double& stddev, std::vector<float>& distances);
288 #ifdef PCL_NO_PRECOMPILE
289 #include <pcl/filters/impl/statistical_outlier_removal.hpp>
292 #endif // PCL_FILTERS_STATISTICAL_OUTLIER_REMOVAL_H_
This file defines compatibility wrappers for low level I/O functions.
boost::shared_ptr< PointCloud< PointT > > Ptr
FilterIndices< PointT >::PointCloud PointCloud
void applyFilter(PointCloud &output)
Filtered results are stored in a separate point cloud.
boost::shared_ptr< pcl::search::Search< PointT > > Ptr
void setStddevMulThresh(double std_mul)
Set the standard deviation multiplier threshold.
PointCloud::ConstPtr PointCloudConstPtr
void setStddevMulThresh(double stddev_mult)
Set the standard deviation multiplier for the distance threshold calculation.
double getStddevMulThresh()
Get the standard deviation multiplier threshold as set by the user.
int getMeanK()
Get the number of nearest neighbors to use for mean distance estimation.
PointCloud represents the base class in PCL for storing collections of 3D points.
void setMeanK(int nr_k)
Set the number of nearest neighbors to use for mean distance estimation.
void applyFilterIndices(std::vector< int > &indices)
Filtered results are indexed by an indices array.
boost::shared_ptr< ::pcl::PCLPointCloud2 const > PCLPointCloud2ConstPtr
A point structure representing Euclidean xyz coordinates, and the RGB color.
pcl::search::Search< PointT >::Ptr SearcherPtr
double getStddevMulThresh()
Get the standard deviation multiplier for the distance threshold calculation.
StatisticalOutlierRemoval(bool extract_removed_indices=false)
Constructor.
double std_mul_
Standard deviations threshold (i.e., points outside of will be marked as outliers).
StatisticalOutlierRemoval(bool extract_removed_indices=false)
Empty constructor.
boost::shared_ptr< StatisticalOutlierRemoval< PointT > > Ptr
FilterIndices represents the base class for filters that are about binary point removal.
boost::shared_ptr< const StatisticalOutlierRemoval< PointT > > ConstPtr
Filter represents the base filter class.
std::string filter_name_
The filter name.
boost::shared_ptr< ::pcl::PCLPointCloud2 > PCLPointCloud2Ptr
boost::shared_ptr< const PointCloud< PointT > > ConstPtr
PointCloud::Ptr PointCloudPtr
StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data.
int getMeanK()
Get the number of points to use for mean distance estimation.
void applyFilter(std::vector< int > &indices)
Filtered results are indexed by an indices array.
KdTreePtr tree_
A pointer to the spatial search object.
boost::shared_ptr< ::pcl::PCLPointCloud2 const > ConstPtr
int mean_k_
The number of points to use for mean distance estimation.
boost::shared_ptr< ::pcl::PCLPointCloud2 > Ptr
void setMeanK(int nr_k)
Set the number of points (k) to use for mean distance estimation.