Point Cloud Library (PCL)  1.8.1-dev
List of all members | Public Member Functions | Protected Member Functions | Protected Attributes
pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar > Class Template Reference

FPCSInitialAlignment computes corresponding four point congruent sets as described in: "4-points congruent sets for robust pairwise surface registration", Dror Aiger, Niloy Mitra, Daniel Cohen-Or. More...

#include <pcl/registration/ia_fpcs.h>

+ Inheritance diagram for pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >:

Public Member Functions

 FPCSInitialAlignment ()
 Constructor. More...
 
virtual ~FPCSInitialAlignment ()
 Destructor. More...
 
void setTargetIndices (const IndicesPtr &target_indices)
 Provide a pointer to the vector of target indices. More...
 
IndicesPtr getTargetIndices () const
 
void setSourceNormals (const NormalsConstPtr &source_normals)
 Provide a pointer to the normals of the source point cloud. More...
 
NormalsConstPtr getSourceNormals () const
 
void setTargetNormals (const NormalsConstPtr &target_normals)
 Provide a pointer to the normals of the target point cloud. More...
 
NormalsConstPtr getTargetNormals () const
 
void setNumberOfThreads (int nr_threads)
 Set the number of used threads if OpenMP is activated. More...
 
int getNumberOfThreads () const
 
void setDelta (float delta, bool normalize=false)
 Set the constant factor delta which weights the internally calculated parameters. More...
 
float getDelta () const
 
void setApproxOverlap (float approx_overlap)
 Set the approximate overlap between source and target. More...
 
float getApproxOverlap () const
 
void setScoreThreshold (float score_threshold)
 Set the scoring threshold used for early finishing the method. More...
 
float getScoreThreshold () const
 
void setNumberOfSamples (int nr_samples)
 Set the number of source samples to use during alignment. More...
 
int getNumberOfSamples () const
 
void setMaxNormalDifference (float max_norm_diff)
 Set the maximum normal difference between valid point correspondences in degree. More...
 
float getMaxNormalDifference () const
 
void setMaxComputationTime (int max_runtime)
 Set the maximum computation time in seconds. More...
 
int getMaxComputationTime () const
 
float getFitnessScore () const
 
- Public Member Functions inherited from pcl::Registration< PointSource, PointTarget, Scalar >
 Registration ()
 Empty constructor. More...
 
virtual ~Registration ()
 destructor. More...
 
void setTransformationEstimation (const TransformationEstimationPtr &te)
 Provide a pointer to the transformation estimation object. More...
 
void setCorrespondenceEstimation (const CorrespondenceEstimationPtr &ce)
 Provide a pointer to the correspondence estimation object. More...
 
void setInputCloud (const PointCloudSourceConstPtr &cloud)
 Provide a pointer to the input source (e.g., the point cloud that we want to align to the target) More...
 
PointCloudSourceConstPtr const getInputCloud ()
 Get a pointer to the input point cloud dataset target. More...
 
virtual void setInputSource (const PointCloudSourceConstPtr &cloud)
 Provide a pointer to the input source (e.g., the point cloud that we want to align to the target) More...
 
PointCloudSourceConstPtr const getInputSource ()
 Get a pointer to the input point cloud dataset target. More...
 
virtual void setInputTarget (const PointCloudTargetConstPtr &cloud)
 Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to) More...
 
PointCloudTargetConstPtr const getInputTarget ()
 Get a pointer to the input point cloud dataset target. More...
 
void setSearchMethodTarget (const KdTreePtr &tree, bool force_no_recompute=false)
 Provide a pointer to the search object used to find correspondences in the target cloud. More...
 
KdTreePtr getSearchMethodTarget () const
 Get a pointer to the search method used to find correspondences in the target cloud. More...
 
void setSearchMethodSource (const KdTreeReciprocalPtr &tree, bool force_no_recompute=false)
 Provide a pointer to the search object used to find correspondences in the source cloud (usually used by reciprocal correspondence finding). More...
 
KdTreeReciprocalPtr getSearchMethodSource () const
 Get a pointer to the search method used to find correspondences in the source cloud. More...
 
Matrix4 getFinalTransformation ()
 Get the final transformation matrix estimated by the registration method. More...
 
Matrix4 getLastIncrementalTransformation ()
 Get the last incremental transformation matrix estimated by the registration method. More...
 
void setMaximumIterations (int nr_iterations)
 Set the maximum number of iterations the internal optimization should run for. More...
 
int getMaximumIterations ()
 Get the maximum number of iterations the internal optimization should run for, as set by the user. More...
 
void setRANSACIterations (int ransac_iterations)
 Set the number of iterations RANSAC should run for. More...
 
double getRANSACIterations ()
 Get the number of iterations RANSAC should run for, as set by the user. More...
 
void setRANSACOutlierRejectionThreshold (double inlier_threshold)
 Set the inlier distance threshold for the internal RANSAC outlier rejection loop. More...
 
double getRANSACOutlierRejectionThreshold ()
 Get the inlier distance threshold for the internal outlier rejection loop as set by the user. More...
 
void setMaxCorrespondenceDistance (double distance_threshold)
 Set the maximum distance threshold between two correspondent points in source <-> target. More...
 
double getMaxCorrespondenceDistance ()
 Get the maximum distance threshold between two correspondent points in source <-> target. More...
 
void setTransformationEpsilon (double epsilon)
 Set the transformation epsilon (maximum allowable translation squared difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution. More...
 
double getTransformationEpsilon ()
 Get the transformation epsilon (maximum allowable translation squared difference between two consecutive transformations) as set by the user. More...
 
void setTransformationRotationEpsilon (double epsilon)
 Set the transformation rotation epsilon (maximum allowable rotation difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution. More...
 
double getTransformationRotationEpsilon ()
 Get the transformation rotation epsilon (maximum allowable difference between two consecutive transformations) as set by the user (epsilon is the cos(angle) in a axis-angle representation). More...
 
void setEuclideanFitnessEpsilon (double epsilon)
 Set the maximum allowed Euclidean error between two consecutive steps in the ICP loop, before the algorithm is considered to have converged. More...
 
double getEuclideanFitnessEpsilon ()
 Get the maximum allowed distance error before the algorithm will be considered to have converged, as set by the user. More...
 
void setPointRepresentation (const PointRepresentationConstPtr &point_representation)
 Provide a boost shared pointer to the PointRepresentation to be used when comparing points. More...
 
template<typename FunctionSignature >
bool registerVisualizationCallback (boost::function< FunctionSignature > &visualizerCallback)
 Register the user callback function which will be called from registration thread in order to update point cloud obtained after each iteration. More...
 
double getFitnessScore (double max_range=std::numeric_limits< double >::max())
 Obtain the Euclidean fitness score (e.g., sum of squared distances from the source to the target) More...
 
double getFitnessScore (const std::vector< float > &distances_a, const std::vector< float > &distances_b)
 Obtain the Euclidean fitness score (e.g., sum of squared distances from the source to the target) from two sets of correspondence distances (distances between source and target points) More...
 
bool hasConverged ()
 Return the state of convergence after the last align run. More...
 
void align (PointCloudSource &output)
 Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output. More...
 
void align (PointCloudSource &output, const Matrix4 &guess)
 Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output. More...
 
const std::string & getClassName () const
 Abstract class get name method. More...
 
bool initCompute ()
 Internal computation initalization. More...
 
bool initComputeReciprocal ()
 Internal computation when reciprocal lookup is needed. More...
 
void addCorrespondenceRejector (const CorrespondenceRejectorPtr &rejector)
 Add a new correspondence rejector to the list. More...
 
std::vector
< CorrespondenceRejectorPtr
getCorrespondenceRejectors ()
 Get the list of correspondence rejectors. More...
 
bool removeCorrespondenceRejector (unsigned int i)
 Remove the i-th correspondence rejector in the list. More...
 
void clearCorrespondenceRejectors ()
 Clear the list of correspondence rejectors. More...
 
- Public Member Functions inherited from pcl::PCLBase< PointSource >
 PCLBase ()
 Empty constructor. More...
 
 PCLBase (const PCLBase &base)
 Copy constructor. More...
 
virtual ~PCLBase ()
 Destructor. More...
 
PointCloudConstPtr const getInputCloud () const
 Get a pointer to the input point cloud dataset. More...
 
virtual void setIndices (const IndicesPtr &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
virtual void setIndices (const IndicesConstPtr &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
virtual void setIndices (const PointIndicesConstPtr &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
virtual void setIndices (size_t row_start, size_t col_start, size_t nb_rows, size_t nb_cols)
 Set the indices for the points laying within an interest region of the point cloud. More...
 
IndicesPtr const getIndices ()
 Get a pointer to the vector of indices used. More...
 
IndicesConstPtr const getIndices () const
 Get a pointer to the vector of indices used. More...
 
const PointSource & operator[] (size_t pos) const
 Override PointCloud operator[] to shorten code. More...
 

Protected Member Functions

virtual void computeTransformation (PointCloudSource &output, const Eigen::Matrix4f &guess)
 Rigid transformation computation method. More...
 
virtual bool initCompute ()
 Internal computation initialization. More...
 
int selectBase (std::vector< int > &base_indices, float(&ratio)[2])
 Select an approximately coplanar set of four points from the source cloud. More...
 
int selectBaseTriangle (std::vector< int > &base_indices)
 Select randomly a triplet of points with large point-to-point distances. More...
 
void setupBase (std::vector< int > &base_indices, float(&ratio)[2])
 Setup the base (four coplanar points) by ordering the points and computing intersection ratios and segment to segment distances of base diagonal. More...
 
float segmentToSegmentDist (const std::vector< int > &base_indices, float(&ratio)[2])
 Calculate intersection ratios and segment to segment distances of base diagonals. More...
 
virtual int bruteForceCorrespondences (int idx1, int idx2, pcl::Correspondences &pairs)
 Search for corresponding point pairs given the distance between two base points. More...
 
virtual int determineBaseMatches (const std::vector< int > &base_indices, std::vector< std::vector< int > > &matches, const pcl::Correspondences &pairs_a, const pcl::Correspondences &pairs_b, const float(&ratio)[2])
 Determine base matches by combining the point pair candidate and search for coinciding intersection points using the diagonal segment ratios of base B. More...
 
int checkBaseMatch (const std::vector< int > &match_indices, const float(&ds)[4])
 Check if outer rectangle distance of matched points fit with the base rectangle. More...
 
virtual void handleMatches (const std::vector< int > &base_indices, std::vector< std::vector< int > > &matches, MatchingCandidates &candidates)
 Method to handle current candidate matches. More...
 
virtual void linkMatchWithBase (const std::vector< int > &base_indices, std::vector< int > &match_indices, pcl::Correspondences &correspondences)
 Sets the correspondences between the base B and the match M by using the distance of each point to the centroid of the rectangle. More...
 
virtual int validateMatch (const std::vector< int > &base_indices, const std::vector< int > &match_indices, const pcl::Correspondences &correspondences, Eigen::Matrix4f &transformation)
 Validate the matching by computing the transformation between the source and target based on the four matched points and by comparing the mean square error (MSE) to a threshold. More...
 
virtual int validateTransformation (Eigen::Matrix4f &transformation, float &fitness_score)
 Validate the transformation by calculating the number of inliers after transforming the source cloud. More...
 
virtual void finalCompute (const std::vector< MatchingCandidates > &candidates)
 Final computation of best match out of vector of best matches. More...
 
- Protected Member Functions inherited from pcl::Registration< PointSource, PointTarget, Scalar >
bool searchForNeighbors (const PointCloudSource &cloud, int index, std::vector< int > &indices, std::vector< float > &distances)
 Search for the closest nearest neighbor of a given point. More...
 
virtual void computeTransformation (PointCloudSource &output, const Matrix4 &guess)=0
 Abstract transformation computation method with initial guess. More...
 
- Protected Member Functions inherited from pcl::PCLBase< PointSource >
bool initCompute ()
 This method should get called before starting the actual computation. More...
 
bool deinitCompute ()
 This method should get called after finishing the actual computation. More...
 

Protected Attributes

NormalsConstPtr source_normals_
 Normals of source point cloud. More...
 
NormalsConstPtr target_normals_
 Normals of target point cloud. More...
 
int nr_threads_
 Number of threads for parallelization (standard = 1). More...
 
float approx_overlap_
 Estimated overlap between source and target (standard = 0.5). More...
 
float delta_
 Delta value of 4pcs algorithm (standard = 1.0). More...
 
float score_threshold_
 Score threshold to stop calculation with success. More...
 
int nr_samples_
 The number of points to uniformly sample the source point cloud. More...
 
float max_norm_diff_
 Maximum normal difference of corresponding point pairs in degrees (standard = 90). More...
 
int max_runtime_
 Maximum allowed computation time in seconds (standard = 0 => ~unlimited). More...
 
float fitness_score_
 Resulting fitness score of the best match. More...
 
float diameter_
 Estimated diamter of the target point cloud. More...
 
float max_base_diameter_sqr_
 Estimated squared metric overlap between source and target. More...
 
bool use_normals_
 Use normals flag. More...
 
bool normalize_delta_
 Normalize delta flag. More...
 
pcl::IndicesPtr source_indices_
 A pointer to the vector of source point indices to use after sampling. More...
 
pcl::IndicesPtr target_indices_
 A pointer to the vector of target point indices to use after sampling. More...
 
float max_pair_diff_
 Maximal difference between corresponding point pairs in source and target. More...
 
float max_edge_diff_
 Maximal difference between the length of the base edges and valid match edges. More...
 
float coincidation_limit_
 Maximal distance between coinciding intersection points to find valid matches. More...
 
float max_mse_
 Maximal mean squared errors of a transformation calculated from a candidate match. More...
 
float max_inlier_dist_sqr_
 Maximal squared point distance between source and target points to count as inlier. More...
 
const float small_error_
 Definition of a small error. More...
 
- Protected Attributes inherited from pcl::Registration< PointSource, PointTarget, Scalar >
std::string reg_name_
 The registration method name. More...
 
KdTreePtr tree_
 A pointer to the spatial search object. More...
 
KdTreeReciprocalPtr tree_reciprocal_
 A pointer to the spatial search object of the source. More...
 
int nr_iterations_
 The number of iterations the internal optimization ran for (used internally). More...
 
int max_iterations_
 The maximum number of iterations the internal optimization should run for. More...
 
int ransac_iterations_
 The number of iterations RANSAC should run for. More...
 
PointCloudTargetConstPtr target_
 The input point cloud dataset target. More...
 
Matrix4 final_transformation_
 The final transformation matrix estimated by the registration method after N iterations. More...
 
Matrix4 transformation_
 The transformation matrix estimated by the registration method. More...
 
Matrix4 previous_transformation_
 The previous transformation matrix estimated by the registration method (used internally). More...
 
double transformation_epsilon_
 The maximum difference between two consecutive transformations in order to consider convergence (user defined). More...
 
double transformation_rotation_epsilon_
 The maximum rotation difference between two consecutive transformations in order to consider convergence (user defined). More...
 
double euclidean_fitness_epsilon_
 The maximum allowed Euclidean error between two consecutive steps in the ICP loop, before the algorithm is considered to have converged. More...
 
double corr_dist_threshold_
 The maximum distance threshold between two correspondent points in source <-> target. More...
 
double inlier_threshold_
 The inlier distance threshold for the internal RANSAC outlier rejection loop. More...
 
bool converged_
 Holds internal convergence state, given user parameters. More...
 
int min_number_correspondences_
 The minimum number of correspondences that the algorithm needs before attempting to estimate the transformation. More...
 
CorrespondencesPtr correspondences_
 The set of correspondences determined at this ICP step. More...
 
TransformationEstimationPtr transformation_estimation_
 A TransformationEstimation object, used to calculate the 4x4 rigid transformation. More...
 
CorrespondenceEstimationPtr correspondence_estimation_
 A CorrespondenceEstimation object, used to estimate correspondences between the source and the target cloud. More...
 
std::vector
< CorrespondenceRejectorPtr
correspondence_rejectors_
 The list of correspondence rejectors to use. More...
 
bool target_cloud_updated_
 Variable that stores whether we have a new target cloud, meaning we need to pre-process it again. More...
 
bool source_cloud_updated_
 Variable that stores whether we have a new source cloud, meaning we need to pre-process it again. More...
 
bool force_no_recompute_
 A flag which, if set, means the tree operating on the target cloud will never be recomputed. More...
 
bool force_no_recompute_reciprocal_
 A flag which, if set, means the tree operating on the source cloud will never be recomputed. More...
 
boost::function< void(const
pcl::PointCloud< PointSource >
&cloud_src, const std::vector
< int > &indices_src, const
pcl::PointCloud< PointTarget >
&cloud_tgt, const std::vector
< int > &indices_tgt)> 
update_visualizer_
 Callback function to update intermediate source point cloud position during it's registration to the target point cloud. More...
 
- Protected Attributes inherited from pcl::PCLBase< PointSource >
PointCloudConstPtr input_
 The input point cloud dataset. More...
 
IndicesPtr indices_
 A pointer to the vector of point indices to use. More...
 
bool use_indices_
 Set to true if point indices are used. More...
 
bool fake_indices_
 If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More...
 

Additional Inherited Members

- Public Types inherited from pcl::Registration< PointSource, PointTarget, Scalar >
typedef Eigen::Matrix< Scalar, 4, 4 > Matrix4
 
typedef boost::shared_ptr
< Registration< PointSource,
PointTarget, Scalar > > 
Ptr
 
typedef boost::shared_ptr
< const Registration
< PointSource, PointTarget,
Scalar > > 
ConstPtr
 
typedef
pcl::registration::CorrespondenceRejector::Ptr 
CorrespondenceRejectorPtr
 
typedef pcl::search::KdTree
< PointTarget > 
KdTree
 
typedef pcl::search::KdTree
< PointTarget >::Ptr 
KdTreePtr
 
typedef pcl::search::KdTree
< PointSource > 
KdTreeReciprocal
 
typedef KdTreeReciprocal::Ptr KdTreeReciprocalPtr
 
typedef pcl::PointCloud
< PointSource > 
PointCloudSource
 
typedef PointCloudSource::Ptr PointCloudSourcePtr
 
typedef PointCloudSource::ConstPtr PointCloudSourceConstPtr
 
typedef pcl::PointCloud
< PointTarget > 
PointCloudTarget
 
typedef PointCloudTarget::Ptr PointCloudTargetPtr
 
typedef PointCloudTarget::ConstPtr PointCloudTargetConstPtr
 
typedef
KdTree::PointRepresentationConstPtr 
PointRepresentationConstPtr
 
typedef
pcl::registration::TransformationEstimation
< PointSource, PointTarget,
Scalar > 
TransformationEstimation
 
typedef
TransformationEstimation::Ptr 
TransformationEstimationPtr
 
typedef
TransformationEstimation::ConstPtr 
TransformationEstimationConstPtr
 
typedef
pcl::registration::CorrespondenceEstimationBase
< PointSource, PointTarget,
Scalar > 
CorrespondenceEstimation
 
typedef
CorrespondenceEstimation::Ptr 
CorrespondenceEstimationPtr
 
typedef
CorrespondenceEstimation::ConstPtr 
CorrespondenceEstimationConstPtr
 
- Public Types inherited from pcl::PCLBase< PointSource >
typedef pcl::PointCloud
< PointSource > 
PointCloud
 
typedef PointCloud::Ptr PointCloudPtr
 
typedef PointCloud::ConstPtr PointCloudConstPtr
 
typedef boost::shared_ptr
< PointIndices
PointIndicesPtr
 
typedef boost::shared_ptr
< PointIndices const > 
PointIndicesConstPtr
 

Detailed Description

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
class pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >

FPCSInitialAlignment computes corresponding four point congruent sets as described in: "4-points congruent sets for robust pairwise surface registration", Dror Aiger, Niloy Mitra, Daniel Cohen-Or.

ACM Transactions on Graphics, vol. 27(3), 2008

Author
P.W.Theiler

Definition at line 77 of file ia_fpcs.h.

Constructor & Destructor Documentation

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::FPCSInitialAlignment ( )

Constructor.

Resets the maximum number of iterations to 0 thus forcing an internal computation if not set by the user. Sets the number of RANSAC iterations to 1000 and the standard transformation estimation to TransformationEstimation3Point.

Definition at line 122 of file ia_fpcs.hpp.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
virtual pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::~FPCSInitialAlignment ( )
inlinevirtual

Destructor.

Definition at line 107 of file ia_fpcs.h.

Member Function Documentation

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::bruteForceCorrespondences ( int  idx1,
int  idx2,
pcl::Correspondences pairs 
)
protectedvirtual

Search for corresponding point pairs given the distance between two base points.

Parameters
[in]idx1first index of current base segment (in source cloud)
[in]idx2second index of current base segment (in source cloud)
[out]pairsresulting point pairs with point-to-point distance close to ref_dist
Returns
  • < 0 no corresponding point pair was found
  • = 0 at least one point pair candidate was found

Definition at line 573 of file ia_fpcs.hpp.

References pcl::euclideanDistance().

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::checkBaseMatch ( const std::vector< int > &  match_indices,
const float(&)  ds[4] 
)
protected

Check if outer rectangle distance of matched points fit with the base rectangle.

Parameters
[in]match_indicesindices of match M
[in]dsedge lengths of base B
Returns
  • < 0 at least one edge of the match M has no corresponding one in the base B
  • = 0 edges of match M fits to the ones of base B

Definition at line 707 of file ia_fpcs.hpp.

References pcl::euclideanDistance().

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::computeTransformation ( PointCloudSource output,
const Eigen::Matrix4f &  guess 
)
protectedvirtual

Rigid transformation computation method.

Parameters
outputthe transformed input point cloud dataset using the rigid transformation found
guessThe computed transforamtion

Definition at line 153 of file ia_fpcs.hpp.

References pcl::StopWatch::getTimeSeconds(), and pcl::transformPointCloud().

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::determineBaseMatches ( const std::vector< int > &  base_indices,
std::vector< std::vector< int > > &  matches,
const pcl::Correspondences pairs_a,
const pcl::Correspondences pairs_b,
const float(&)  ratio[2] 
)
protectedvirtual

Determine base matches by combining the point pair candidate and search for coinciding intersection points using the diagonal segment ratios of base B.

The coincidation threshold is calculated during initialization (coincidation_limit_).

Parameters
[in]base_indicesindices of base B
[out]matchesvector of candidate matches w.r.t the base B
[in]pairs_apoint pairs corresponding to points of 1st diagonal of base B
[in]pairs_bpoint pairs corresponding to points of 2nd diagonal of base B
[in]ratiodiagonal intersection ratios of base points
Returns
  • < 0 no base match could be found
  • = 0 at least one base match was found

Definition at line 627 of file ia_fpcs.hpp.

References pcl::euclideanDistance().

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::finalCompute ( const std::vector< MatchingCandidates > &  candidates)
protectedvirtual

Final computation of best match out of vector of best matches.

To avoid cross thread dependencies during parallel running, a best match for each try was calculated.

Note
For forwards compatibility the candidates are stored in vectors of 'vectors of size 1'.
Parameters
[in]candidatesvector of candidate matches

Reimplemented in pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >.

Definition at line 885 of file ia_fpcs.hpp.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getApproxOverlap ( ) const
inline
Returns
the approximated overlap between source and target.

Definition at line 209 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::approx_overlap_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getDelta ( ) const
inline
Returns
the constant factor delta which weights the internally calculated parameters.

Definition at line 192 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::delta_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getFitnessScore ( ) const
inline
Returns
the fitness score of the best scored four-point match.

Definition at line 285 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::fitness_score_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getMaxComputationTime ( ) const
inline
Returns
the maximum computation time in seconds.

Definition at line 277 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_runtime_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getMaxNormalDifference ( ) const
inline
Returns
the maximum normal difference between valid point correspondences in degree.

Definition at line 260 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_norm_diff_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getNumberOfSamples ( ) const
inline
Returns
the number of source samples to use during alignment.

Definition at line 243 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::nr_samples_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getNumberOfThreads ( ) const
inline
Returns
the number of threads used if OpenMP is activated.

Definition at line 173 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::nr_threads_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getScoreThreshold ( ) const
inline
Returns
the scoring threshold used for early finishing the method.

Definition at line 226 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::score_threshold_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
NormalsConstPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getSourceNormals ( ) const
inline
Returns
the normals of the source point cloud.

Definition at line 139 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::source_normals_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
IndicesPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getTargetIndices ( ) const
inline
Returns
a pointer to the vector of target indices.

Definition at line 122 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::target_indices_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
NormalsConstPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getTargetNormals ( ) const
inline
Returns
the normals of the target point cloud.

Definition at line 156 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::target_normals_.

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::handleMatches ( const std::vector< int > &  base_indices,
std::vector< std::vector< int > > &  matches,
MatchingCandidates candidates 
)
protectedvirtual

Method to handle current candidate matches.

Here we validate and evaluate the matches w.r.t the base and store the best fitting match (together with its score and estimated transformation).

Note
For forwards compatibility the results are stored in 'vectors of size 1'.
Parameters
[in]base_indicesindices of base B
[in,out]matchesvector of candidate matches w.r.t the base B. The candidate matches are reordered during this step.
[out]candidatesvector which contains the candidates matches M

Reimplemented in pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >.

Definition at line 724 of file ia_fpcs.hpp.

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
bool pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::initCompute ( )
protectedvirtual

Internal computation initialization.

Reimplemented in pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >.

Definition at line 232 of file ia_fpcs.hpp.

References pcl::getMinMax3D().

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::linkMatchWithBase ( const std::vector< int > &  base_indices,
std::vector< int > &  match_indices,
pcl::Correspondences correspondences 
)
protectedvirtual

Sets the correspondences between the base B and the match M by using the distance of each point to the centroid of the rectangle.

Parameters
[in]base_indicesindices of base B
[in]match_indicesindices of match M
[out]correspondencesresulting correspondences

Definition at line 760 of file ia_fpcs.hpp.

References pcl::compute3DCentroid(), and pcl::squaredEuclideanDistance().

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::segmentToSegmentDist ( const std::vector< int > &  base_indices,
float(&)  ratio[2] 
)
protected

Calculate intersection ratios and segment to segment distances of base diagonals.

Parameters
[in]base_indicesindices of base B
[out]ratiodiagonal intersection ratios of base points
Returns
quality value of diagonal intersection

Definition at line 482 of file ia_fpcs.hpp.

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::selectBase ( std::vector< int > &  base_indices,
float(&)  ratio[2] 
)
protected

Select an approximately coplanar set of four points from the source cloud.

Parameters
[out]base_indicesselected source cloud indices, further used as base (B)
[out]ratiothe two diagonal intersection ratios (r1,r2) of the base points
Returns
  • < 0 no coplanar four point sets with large enough sampling distance was found
  • = 0 a set of four congruent points was selected

Definition at line 334 of file ia_fpcs.hpp.

References pcl::compute3DCentroid(), pcl::SampleConsensusModelPlane< PointT >::computeModelCoefficients(), pcl::pointToPlaneDistance(), pcl::SampleConsensusModel< PointT >::setIndices(), and pcl::squaredEuclideanDistance().

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::selectBaseTriangle ( std::vector< int > &  base_indices)
protected

Select randomly a triplet of points with large point-to-point distances.

The minimum point sampling distance is calculated based on the estimated point cloud overlap during initialization.

Parameters
[out]base_indicesindices of base B
Returns
  • < 0 no triangle with large enough base lines could be selected
  • = 0 base triangle succesully selected

Definition at line 401 of file ia_fpcs.hpp.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setApproxOverlap ( float  approx_overlap)
inline

Set the approximate overlap between source and target.

Parameters
[in]approx_overlapthe estimated overlap

Definition at line 202 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::approx_overlap_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setDelta ( float  delta,
bool  normalize = false 
)
inline

Set the constant factor delta which weights the internally calculated parameters.

Parameters
[in]deltathe weight factor delta
[in]normalizeflag if delta should be normalized according to point cloud density

Definition at line 184 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::delta_, and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::normalize_delta_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setMaxComputationTime ( int  max_runtime)
inline

Set the maximum computation time in seconds.

Parameters
[in]max_runtimethe maximum runtime of the method in seconds

Definition at line 270 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_runtime_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setMaxNormalDifference ( float  max_norm_diff)
inline

Set the maximum normal difference between valid point correspondences in degree.

Parameters
[in]max_norm_diffthe maximum difference in degree

Definition at line 253 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_norm_diff_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setNumberOfSamples ( int  nr_samples)
inline

Set the number of source samples to use during alignment.

Parameters
[in]nr_samplesthe number of source samples

Definition at line 236 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::nr_samples_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setNumberOfThreads ( int  nr_threads)
inline

Set the number of used threads if OpenMP is activated.

Parameters
[in]nr_threadsthe number of used threads

Definition at line 166 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::nr_threads_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setScoreThreshold ( float  score_threshold)
inline

Set the scoring threshold used for early finishing the method.

Parameters
[in]score_thresholdearly terminating score criteria

Definition at line 219 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::score_threshold_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setSourceNormals ( const NormalsConstPtr &  source_normals)
inline

Provide a pointer to the normals of the source point cloud.

Parameters
[in]source_normalspointer to the normals of the source pointer cloud.

Definition at line 132 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::source_normals_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setTargetIndices ( const IndicesPtr target_indices)
inline

Provide a pointer to the vector of target indices.

Parameters
[in]target_indicesa pointer to the target indices

Definition at line 115 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::target_indices_.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setTargetNormals ( const NormalsConstPtr &  target_normals)
inline

Provide a pointer to the normals of the target point cloud.

Parameters
[in]target_normalspoint to the normals of the target point cloud.

Definition at line 149 of file ia_fpcs.h.

References pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::target_normals_.

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
void pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setupBase ( std::vector< int > &  base_indices,
float(&)  ratio[2] 
)
protected

Setup the base (four coplanar points) by ordering the points and computing intersection ratios and segment to segment distances of base diagonal.

Parameters
[in,out]base_indicesindices of base B (will be reordered)
[out]ratiodiagonal intersection ratios of base points

Definition at line 436 of file ia_fpcs.hpp.

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateMatch ( const std::vector< int > &  base_indices,
const std::vector< int > &  match_indices,
const pcl::Correspondences correspondences,
Eigen::Matrix4f &  transformation 
)
protectedvirtual

Validate the matching by computing the transformation between the source and target based on the four matched points and by comparing the mean square error (MSE) to a threshold.

The MSE limit was calculated during initialization (max_mse_).

Parameters
[in]base_indicesindices of base B
[in]match_indicesindices of match M
[in]correspondencescorresondences between source and target
[out]transformationresulting transformation matrix
Returns
  • < 0 MSE bigger than max_mse_
  • = 0 MSE smaller than max_mse_

Definition at line 814 of file ia_fpcs.hpp.

References pcl::PointCloud< T >::points, pcl::squaredEuclideanDistance(), and pcl::transformPointCloud().

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation ( Eigen::Matrix4f &  transformation,
float &  fitness_score 
)
protectedvirtual

Validate the transformation by calculating the number of inliers after transforming the source cloud.

The resulting fitness score is later used as the decision criteria of the best fitting match.

Parameters
[out]transformationupdated orientation matrix using all inliers
[out]fitness_scorecurrent best fitness_score
Note
fitness score is only updated if the score of the current transformation exceeds the input one.
Returns
  • < 0 if previous result is better than the current one (score remains)
  • = 0 current result is better than the previous one (score updated)

Reimplemented in pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >.

Definition at line 844 of file ia_fpcs.hpp.

References pcl::PointCloud< T >::begin(), pcl::PointCloud< T >::size(), and pcl::transformPointCloud().

Member Data Documentation

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::approx_overlap_
protected
template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::coincidation_limit_
protected

Maximal distance between coinciding intersection points to find valid matches.

Note
Internally calculated using an estimation of the point density.

Definition at line 548 of file ia_fpcs.h.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::delta_
protected

Delta value of 4pcs algorithm (standard = 1.0).

It can be used as:

  • absolute value (normalization = false), value should represent the point accuracy to ensure finding neighbors between source <-> target
  • relative value (normalization = true), to adjust the internally calculated point accuracy (= point density)

Definition at line 491 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getDelta(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setDelta().

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::diameter_
protected

Estimated diamter of the target point cloud.

Definition at line 513 of file ia_fpcs.h.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::fitness_score_
protected

Resulting fitness score of the best match.

Definition at line 509 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getFitnessScore().

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_base_diameter_sqr_
protected

Estimated squared metric overlap between source and target.

Note
Internally calculated using the estimated overlap and the extent of the source cloud. It is used to derive the minimum sampling distance of the base points as well as to calculated the number of trys to reliable find a correct mach.

Definition at line 520 of file ia_fpcs.h.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_edge_diff_
protected

Maximal difference between the length of the base edges and valid match edges.

Note
Internally calculated using an estimation of the point density.

Definition at line 543 of file ia_fpcs.h.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_inlier_dist_sqr_
protected

Maximal squared point distance between source and target points to count as inlier.

Note
Internally calculated using an estimation of the point density.

Definition at line 558 of file ia_fpcs.h.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_mse_
protected

Maximal mean squared errors of a transformation calculated from a candidate match.

Note
Internally calculated using an estimation of the point density.

Definition at line 553 of file ia_fpcs.h.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_norm_diff_
protected
template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_pair_diff_
protected

Maximal difference between corresponding point pairs in source and target.

Note
Internally calculated using an estimation of the point density.

Definition at line 538 of file ia_fpcs.h.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::max_runtime_
protected
template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
bool pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::normalize_delta_
protected
template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::nr_samples_
protected
template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
int pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::nr_threads_
protected

Number of threads for parallelization (standard = 1).

Note
Only used if run compiled with OpenMP.

Definition at line 481 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getNumberOfThreads(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setNumberOfThreads().

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::score_threshold_
protected

Score threshold to stop calculation with success.

If not set by the user it is equal to the approximated overlap

Definition at line 496 of file ia_fpcs.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::getScoreThreshold(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::setScoreThreshold().

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
const float pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::small_error_
protected

Definition of a small error.

Definition at line 562 of file ia_fpcs.h.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
pcl::IndicesPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::source_indices_
protected

A pointer to the vector of source point indices to use after sampling.

Definition at line 530 of file ia_fpcs.h.

template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
NormalsConstPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::source_normals_
protected
template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
pcl::IndicesPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::target_indices_
protected
template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
NormalsConstPtr pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::target_normals_
protected
template<typename PointSource, typename PointTarget, typename NormalT = pcl::Normal, typename Scalar = float>
bool pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::use_normals_
protected

Use normals flag.

Definition at line 523 of file ia_fpcs.h.


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