SampleConsensusInitialAlignment is an implementation of the initial alignment algorithm described in section IV of "Fast Point Feature Histograms (FPFH) for 3D Registration," Rusu et al. More...
#include <ia_ransac.h>
Public Member Functions | |
| float | getMinSampleDistance () |
| Get the minimum distances between samples, as set by the user. | |
| int | getNumberOfSamples () |
| Set the number of samples to use during each iteration, as set by the user. | |
| FeatureCloudConstPtr const | getSourceFeatures () |
| Get a pointer to the source point cloud's features. | |
| FeatureCloudConstPtr const | getTargetFeatures () |
| Get a pointer to the target point cloud's features. | |
| SampleConsensusInitialAlignment () | |
| Constructor. | |
| void | setMinSampleDistance (float min_sample_distance) |
| Set the minimum distances between samples. | |
| void | setNumberOfSamples (int nr_samples) |
| Set the number of samples to use during each iteration. | |
| void | setSourceFeatures (const FeatureCloudConstPtr &features) |
| Provide a boost shared pointer to the source point cloud's feature descriptors. | |
| void | setTargetFeatures (const FeatureCloudConstPtr &features) |
| Provide a boost shared pointer to the target point cloud's feature descriptors. | |
Protected Member Functions | |
| virtual void | computeTransformation (PointCloudSource &output) |
| Rigid transformation computation method. | |
Protected Attributes | |
| FeatureKdTreePtr | feature_tree_ |
| The KdTree used to compare feature descriptors. | |
| FeatureCloudConstPtr | input_features_ |
| The source point cloud's feature descriptors. | |
| float | min_sample_distance_ |
| The minimum distances between samples. | |
| int | nr_samples_ |
| The number of samples to use during each iteration. | |
| FeatureCloudConstPtr | target_features_ |
| The target point cloud's feature descriptors. | |
Private Types | |
| typedef pcl::PointCloud< FeatureT > | FeatureCloud |
| typedef FeatureCloud::ConstPtr | FeatureCloudConstPtr |
| typedef FeatureCloud::Ptr | FeatureCloudPtr |
| typedef KdTreeFLANN< FeatureT > ::Ptr | FeatureKdTreePtr |
| typedef Registration < PointSource, PointTarget > ::PointCloudSource | PointCloudSource |
| typedef PointCloudSource::ConstPtr | PointCloudSourceConstPtr |
| typedef PointCloudSource::Ptr | PointCloudSourcePtr |
| typedef Registration < PointSource, PointTarget > ::PointCloudTarget | PointCloudTarget |
| typedef PointIndices::ConstPtr | PointIndicesConstPtr |
| typedef PointIndices::Ptr | PointIndicesPtr |
Private Member Functions | |
| float | computeErrorMetric (const PointCloudSource &cloud, float threshold) |
| An error metric for that computes the quality of the alignment between the given cloud and the target. | |
| void | findSimilarFeatures (const FeatureCloud &input_features, const std::vector< int > &sample_indices, std::vector< int > &corresponding_indices) |
| For each of the sample points, find a list of points in the target cloud whose features are similar to the sample points' features. From these, select one randomly which will be considered that sample point's correspondence. | |
| int | getRandomIndex (int n) |
| Choose a random index between 0 and n-1. | |
| void | selectSamples (const PointCloudSource &cloud, int nr_samples, float min_sample_distance, std::vector< int > &sample_indices) |
| Select nr_samples sample points from cloud while making sure that their pairwise distances are greater than a user-defined minimum distance, min_sample_distance. | |
SampleConsensusInitialAlignment is an implementation of the initial alignment algorithm described in section IV of "Fast Point Feature Histograms (FPFH) for 3D Registration," Rusu et al.
Definition at line 52 of file ia_ransac.h.
typedef pcl::PointCloud<FeatureT> pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::FeatureCloud [private] |
Definition at line 75 of file ia_ransac.h.
typedef FeatureCloud::ConstPtr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::FeatureCloudConstPtr [private] |
Definition at line 77 of file ia_ransac.h.
typedef FeatureCloud::Ptr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::FeatureCloudPtr [private] |
Definition at line 76 of file ia_ransac.h.
typedef KdTreeFLANN<FeatureT>::Ptr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::FeatureKdTreePtr [private] |
Definition at line 79 of file ia_ransac.h.
typedef Registration<PointSource, PointTarget>::PointCloudSource pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::PointCloudSource [private] |
Reimplemented from pcl::Registration< PointSource, PointTarget >.
Definition at line 66 of file ia_ransac.h.
typedef PointCloudSource::ConstPtr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::PointCloudSourceConstPtr [private] |
Reimplemented from pcl::Registration< PointSource, PointTarget >.
Definition at line 68 of file ia_ransac.h.
typedef PointCloudSource::Ptr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::PointCloudSourcePtr [private] |
Reimplemented from pcl::Registration< PointSource, PointTarget >.
Definition at line 67 of file ia_ransac.h.
typedef Registration<PointSource, PointTarget>::PointCloudTarget pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::PointCloudTarget [private] |
Reimplemented from pcl::Registration< PointSource, PointTarget >.
Definition at line 70 of file ia_ransac.h.
typedef PointIndices::ConstPtr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::PointIndicesConstPtr [private] |
Reimplemented from pcl::PCLBase< PointSource >.
Definition at line 73 of file ia_ransac.h.
typedef PointIndices::Ptr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::PointIndicesPtr [private] |
Reimplemented from pcl::PCLBase< PointSource >.
Definition at line 72 of file ia_ransac.h.
| pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::SampleConsensusInitialAlignment | ( | ) | [inline] |
Constructor.
Definition at line 84 of file ia_ransac.h.
| float pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::computeErrorMetric | ( | const PointCloudSource & | cloud, | |
| float | threshold | |||
| ) | [inline, private] |
An error metric for that computes the quality of the alignment between the given cloud and the target.
| cloud | the input cloud | |
| threshold | distances greater than this value are capped |
Definition at line 147 of file ia_ransac.hpp.
| void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::computeTransformation | ( | PointCloudSource & | output | ) | [inline, protected, virtual] |
Rigid transformation computation method.
| output | the transformed input point cloud dataset using the rigid transformation found |
Implements pcl::Registration< PointSource, PointTarget >.
Definition at line 182 of file ia_ransac.hpp.
| void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::findSimilarFeatures | ( | const FeatureCloud & | input_features, | |
| const std::vector< int > & | sample_indices, | |||
| std::vector< int > & | corresponding_indices | |||
| ) | [inline, private] |
For each of the sample points, find a list of points in the target cloud whose features are similar to the sample points' features. From these, select one randomly which will be considered that sample point's correspondence.
| input_features | a cloud of feature descriptors | |
| sample_indices | the indices of each sample point | |
| corresponding_indices | the resulting indices of each sample's corresponding point in the target cloud |
Definition at line 126 of file ia_ransac.hpp.
| float pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::getMinSampleDistance | ( | ) | [inline] |
Get the minimum distances between samples, as set by the user.
Definition at line 118 of file ia_ransac.h.
| int pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::getNumberOfSamples | ( | ) | [inline] |
Set the number of samples to use during each iteration, as set by the user.
Definition at line 128 of file ia_ransac.h.
| int pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::getRandomIndex | ( | int | n | ) | [inline, private] |
Choose a random index between 0 and n-1.
| n | the number of possible indices to choose from |
Definition at line 135 of file ia_ransac.h.
| FeatureCloudConstPtr const pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::getSourceFeatures | ( | ) | [inline] |
Get a pointer to the source point cloud's features.
Definition at line 98 of file ia_ransac.h.
| FeatureCloudConstPtr const pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::getTargetFeatures | ( | ) | [inline] |
Get a pointer to the target point cloud's features.
Definition at line 108 of file ia_ransac.h.
| void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::selectSamples | ( | const PointCloudSource & | cloud, | |
| int | nr_samples, | |||
| float | min_sample_distance, | |||
| std::vector< int > & | sample_indices | |||
| ) | [inline, private] |
Select nr_samples sample points from cloud while making sure that their pairwise distances are greater than a user-defined minimum distance, min_sample_distance.
| cloud | the input point cloud | |
| nr_samples | the number of samples to select | |
| min_sample_distance | the minimum distance between any two samples | |
| sample_indices | the resulting sample indices |
Definition at line 67 of file ia_ransac.hpp.
| void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::setMinSampleDistance | ( | float | min_sample_distance | ) | [inline] |
Set the minimum distances between samples.
| min_sample_distance | the minimum distances between samples |
Definition at line 114 of file ia_ransac.h.
| void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::setNumberOfSamples | ( | int | nr_samples | ) | [inline] |
Set the number of samples to use during each iteration.
| nr_samples | the number of samples to use during each iteration |
Definition at line 124 of file ia_ransac.h.
| void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::setSourceFeatures | ( | const FeatureCloudConstPtr & | features | ) | [inline] |
Provide a boost shared pointer to the source point cloud's feature descriptors.
| features | the source point cloud's features |
Definition at line 40 of file ia_ransac.hpp.
| void pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::setTargetFeatures | ( | const FeatureCloudConstPtr & | features | ) | [inline] |
Provide a boost shared pointer to the target point cloud's feature descriptors.
| features | the target point cloud's features |
Definition at line 53 of file ia_ransac.hpp.
FeatureKdTreePtr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::feature_tree_ [protected] |
The KdTree used to compare feature descriptors.
Definition at line 187 of file ia_ransac.h.
FeatureCloudConstPtr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::input_features_ [protected] |
The source point cloud's feature descriptors.
Definition at line 175 of file ia_ransac.h.
float pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::min_sample_distance_ [protected] |
The minimum distances between samples.
Definition at line 184 of file ia_ransac.h.
int pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::nr_samples_ [protected] |
The number of samples to use during each iteration.
Definition at line 181 of file ia_ransac.h.
FeatureCloudConstPtr pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::target_features_ [protected] |
The target point cloud's feature descriptors.
Definition at line 178 of file ia_ransac.h.
