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;
180 SearcherPtr searcher_;
220 std_mul_ (0.0), tree_ ()
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_ 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.
void applyFilter(PointCloud &output)
Filtered results are stored in a separate point cloud.
PointCloud::ConstPtr PointCloudConstPtr
This file defines compatibility wrappers for low level I/O functions.
int getMeanK()
Get the number of nearest neighbors to use for mean distance estimation.
double getStddevMulThresh()
Get the standard deviation multiplier threshold as set by the user.
void applyFilterIndices(std::vector< int > &indices)
Filtered results are indexed by an indices array.
void setStddevMulThresh(double stddev_mult)
Set the standard deviation multiplier for the distance threshold calculation.
boost::shared_ptr< ::pcl::PCLPointCloud2 const > PCLPointCloud2ConstPtr
void setMeanK(int nr_k)
Set the number of nearest neighbors to use for mean distance estimation.
boost::shared_ptr< ::pcl::PCLPointCloud2 > Ptr
pcl::search::Search< PointT >::Ptr SearcherPtr
boost::shared_ptr< PointCloud< PointT > > Ptr
double getStddevMulThresh()
Get the standard deviation multiplier for the distance threshold calculation.
FilterIndices represents the base class for filters that are about binary point removal.
StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data.
boost::shared_ptr< StatisticalOutlierRemoval< PointT > > Ptr
StatisticalOutlierRemoval(bool extract_removed_indices=false)
Constructor.
Filter represents the base filter class.
boost::shared_ptr< pcl::search::Search< PointT > > Ptr
StatisticalOutlierRemoval(bool extract_removed_indices=false)
Empty constructor.
double std_mul_
Standard deviations threshold (i.e., points outside of will be marked as outliers).
boost::shared_ptr< const PointCloud< PointT > > ConstPtr
boost::shared_ptr< ::pcl::PCLPointCloud2 const > ConstPtr
PointCloud represents the base class in PCL for storing collections of 3D points. ...
boost::shared_ptr< ::pcl::PCLPointCloud2 > PCLPointCloud2Ptr
int getMeanK()
Get the number of points to use for mean distance estimation.
KdTreePtr tree_
A pointer to the spatial search object.
boost::shared_ptr< const StatisticalOutlierRemoval< PointT > > ConstPtr
PointCloud::Ptr PointCloudPtr
std::string filter_name_
The filter name.
A point structure representing Euclidean xyz coordinates, and the RGB color.
FilterIndices< PointT >::PointCloud PointCloud
void applyFilter(std::vector< int > &indices)
Filtered results are indexed by an indices array.
int mean_k_
The number of points to use for mean distance estimation.