Point Cloud Library (PCL)  1.7.0
Public Types | Public Member Functions
pcl::StatisticalMultiscaleInterestRegionExtraction< PointT > Class Template Reference

Class for extracting interest regions from unstructured point clouds, based on a multi scale statistical approach. More...

#include <pcl/features/statistical_multiscale_interest_region_extraction.h>

+ Inheritance diagram for pcl::StatisticalMultiscaleInterestRegionExtraction< PointT >:

List of all members.

Public Types

typedef boost::shared_ptr
< std::vector< int > > 
IndicesPtr
typedef boost::shared_ptr
< StatisticalMultiscaleInterestRegionExtraction
< PointT > > 
Ptr
typedef boost::shared_ptr
< const
StatisticalMultiscaleInterestRegionExtraction
< PointT > > 
ConstPtr

Public Member Functions

 StatisticalMultiscaleInterestRegionExtraction ()
 Empty constructor.
void generateCloudGraph ()
 Method that generates the underlying nearest neighbor graph based on the input point cloud.
void computeRegionsOfInterest (std::list< IndicesPtr > &rois)
 The method to be called in order to run the algorithm and produce the resulting set of regions of interest.
void setScalesVector (std::vector< float > &scale_values)
 Method for setting the scale parameters for the algorithm.
std::vector< float > getScalesVector ()
 Method for getting the scale parameters vector.

Detailed Description

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

Class for extracting interest regions from unstructured point clouds, based on a multi scale statistical approach.

Please refer to the following publications for more details: Ranjith Unnikrishnan and Martial Hebert Multi-Scale Interest Regions from Unorganized Point Clouds Workshop on Search in 3D (S3D), IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) June, 2008

Statistical Approaches to Multi-scale Point Cloud Processing Ranjith Unnikrishnan PhD Thesis The Robotics Institute Carnegie Mellon University May, 2008

Author:
Alexandru-Eugen Ichim

Definition at line 65 of file statistical_multiscale_interest_region_extraction.h.


Member Typedef Documentation

template<typename PointT >
typedef boost::shared_ptr<std::vector<int> > pcl::StatisticalMultiscaleInterestRegionExtraction< PointT >::IndicesPtr

Constructor & Destructor Documentation

Empty constructor.

Definition at line 74 of file statistical_multiscale_interest_region_extraction.h.


Member Function Documentation

template<typename PointT >
void pcl::StatisticalMultiscaleInterestRegionExtraction< PointT >::computeRegionsOfInterest ( std::list< IndicesPtr > &  rois)

The method to be called in order to run the algorithm and produce the resulting set of regions of interest.

Definition at line 122 of file statistical_multiscale_interest_region_extraction.hpp.

Method that generates the underlying nearest neighbor graph based on the input point cloud.

Definition at line 53 of file statistical_multiscale_interest_region_extraction.hpp.

References pcl::KdTreeFLANN< PointT, Dist >::nearestKSearch(), and pcl::KdTreeFLANN< PointT, Dist >::setInputCloud().

template<typename PointT >
std::vector<float> pcl::StatisticalMultiscaleInterestRegionExtraction< PointT >::getScalesVector ( ) [inline]

Method for getting the scale parameters vector.

Definition at line 98 of file statistical_multiscale_interest_region_extraction.h.

template<typename PointT >
void pcl::StatisticalMultiscaleInterestRegionExtraction< PointT >::setScalesVector ( std::vector< float > &  scale_values) [inline]

Method for setting the scale parameters for the algorithm.

Parameters:
scale_valuesvector of scales to determine the size of each scaling step

Definition at line 94 of file statistical_multiscale_interest_region_extraction.h.


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