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;
221 std_mul_ (0.0), tree_ (), negative_ (false)
223 filter_name_ =
"StatisticalOutlierRemoval";
267 negative_ = negative;
300 #ifdef PCL_NO_PRECOMPILE
301 #include <pcl/filters/impl/statistical_outlier_removal.hpp>
304 #endif // PCL_FILTERS_STATISTICAL_OUTLIER_REMOVAL_H_
void applyFilter(std::vector< int > &indices)
Filtered results are indexed by an indices array.
boost::shared_ptr< ::pcl::PCLPointCloud2 > Ptr
int getMeanK()
Get the number of nearest neighbors to use for mean distance estimation.
PointCloud::ConstPtr PointCloudConstPtr
int mean_k_
The number of points to use for mean distance estimation.
PointCloud::Ptr PointCloudPtr
std::string filter_name_
The filter name.
int getMeanK()
Get the number of points to use for mean distance estimation.
Filter represents the base filter class.
FilterIndices< PointT >::PointCloud PointCloud
bool negative_
If true, the outliers will be returned instead of the inliers (default: false).
StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data.
boost::shared_ptr< ::pcl::PCLPointCloud2 const > PCLPointCloud2ConstPtr
boost::shared_ptr< ::pcl::PCLPointCloud2 const > ConstPtr
void setMeanK(int nr_k)
Set 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.
StatisticalOutlierRemoval(bool extract_removed_indices=false)
Empty constructor.
void setNegative(bool negative)
Set whether the indices should be returned, or all points except the indices.
FilterIndices represents the base class for filters that are about binary point removal.
void applyFilter(PointCloud &output)
Filtered results are stored in a separate point cloud.
pcl::search::Search< PointT >::Ptr SearcherPtr
boost::shared_ptr< pcl::search::Search< PointT > > Ptr
boost::shared_ptr< PointCloud< PointT > > Ptr
double getStddevMulThresh()
Get the standard deviation multiplier threshold as set by the user.
KdTreePtr tree_
A pointer to the spatial search object.
bool getNegative()
Get the value of the internal negative_ parameter.
boost::shared_ptr< ::pcl::PCLPointCloud2 > PCLPointCloud2Ptr
boost::shared_ptr< StatisticalOutlierRemoval< PointT > > Ptr
void setMeanK(int nr_k)
Set the number of points (k) to use for mean distance estimation.
boost::shared_ptr< const PointCloud< PointT > > ConstPtr
double std_mul_
Standard deviations threshold (i.e., points outside of will be marked as outliers).
void setStddevMulThresh(double std_mul)
Set the standard deviation multiplier threshold.
double getStddevMulThresh()
Get the standard deviation multiplier for the distance threshold calculation.
void applyFilterIndices(std::vector< int > &indices)
Filtered results are indexed by an indices array.
boost::shared_ptr< const StatisticalOutlierRemoval< PointT > > ConstPtr
StatisticalOutlierRemoval(bool extract_removed_indices=false)
Constructor.
A point structure representing Euclidean xyz coordinates, and the RGB color.