Point Cloud Library (PCL)  1.9.0-dev
Classes | Typedefs | Functions
pcl::registration Namespace Reference

Classes

struct  by_score
 Sorting of candidates based on fitness score value. More...
 
class  ConvergenceCriteria
 ConvergenceCriteria represents an abstract base class for different convergence criteria used in registration loops. More...
 
class  CorrespondenceEstimation
 CorrespondenceEstimation represents the base class for determining correspondences between target and query point sets/features. More...
 
class  CorrespondenceEstimationBackProjection
 CorrespondenceEstimationBackprojection computes correspondences as points in the target cloud which have minimum More...
 
class  CorrespondenceEstimationBase
 Abstract CorrespondenceEstimationBase class. More...
 
class  CorrespondenceEstimationNormalShooting
 CorrespondenceEstimationNormalShooting computes correspondences as points in the target cloud which have minimum distance to normals computed on the input cloud More...
 
class  CorrespondenceEstimationOrganizedProjection
 CorrespondenceEstimationOrganizedProjection computes correspondences by projecting the source point cloud onto the target point cloud using the camera intrinsic and extrinsic parameters. More...
 
class  CorrespondenceRejectionOrganizedBoundary
 The CorrespondenceRejectionOrganizedBoundary class implements a simple correspondence rejection measure. More...
 
class  CorrespondenceRejector
 CorrespondenceRejector represents the base class for correspondence rejection methods More...
 
class  CorrespondenceRejectorDistance
 CorrespondenceRejectorDistance implements a simple correspondence rejection method based on thresholding the distances between the correspondences. More...
 
class  CorrespondenceRejectorFeatures
 CorrespondenceRejectorFeatures implements a correspondence rejection method based on a set of feature descriptors. More...
 
class  CorrespondenceRejectorMedianDistance
 CorrespondenceRejectorMedianDistance implements a simple correspondence rejection method based on thresholding based on the median distance between the correspondences. More...
 
class  CorrespondenceRejectorOneToOne
 CorrespondenceRejectorOneToOne implements a correspondence rejection method based on eliminating duplicate match indices in the correspondences. More...
 
class  CorrespondenceRejectorPoly
 CorrespondenceRejectorPoly implements a correspondence rejection method that exploits low-level and pose-invariant geometric constraints between two point sets by forming virtual polygons of a user-specifiable cardinality on each model using the input correspondences. More...
 
class  CorrespondenceRejectorSampleConsensus
 CorrespondenceRejectorSampleConsensus implements a correspondence rejection using Random Sample Consensus to identify inliers (and reject outliers) More...
 
class  CorrespondenceRejectorSampleConsensus2D
 CorrespondenceRejectorSampleConsensus2D implements a pixel-based correspondence rejection using Random Sample Consensus to identify inliers (and reject outliers) More...
 
class  CorrespondenceRejectorSurfaceNormal
 CorrespondenceRejectorSurfaceNormal implements a simple correspondence rejection method based on the angle between the normals at correspondent points. More...
 
class  CorrespondenceRejectorTrimmed
 CorrespondenceRejectorTrimmed implements a correspondence rejection for ICP-like registration algorithms that uses only the best 'k' correspondences where 'k' is some estimate of the overlap between the two point clouds being registered. More...
 
class  CorrespondenceRejectorVarTrimmed
 CorrespondenceRejectoVarTrimmed implements a simple correspondence rejection method by considering as inliers a certain percentage of correspondences with the least distances. More...
 
class  DataContainer
 DataContainer is a container for the input and target point clouds and implements the interface to compute correspondence scores between correspondent points in the input and target clouds More...
 
class  DataContainerInterface
 DataContainerInterface provides a generic interface for computing correspondence scores between correspondent points in the input and target clouds More...
 
class  DefaultConvergenceCriteria
 DefaultConvergenceCriteria represents an instantiation of ConvergenceCriteria, and implements the following criteria for registration loop evaluation: More...
 
class  ELCH
 ELCH (Explicit Loop Closing Heuristic) class More...
 
class  FPCSInitialAlignment
 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...
 
class  GraphHandler
 GraphHandler class is a wrapper for a general SLAM graph The actual graph class must fulfill the following boost::graph concepts: More...
 
class  GraphOptimizer
 GraphOptimizer class; derive and specialize for each graph type More...
 
class  IncrementalRegistration
 Incremental IterativeClosestPoint class. More...
 
class  KFPCSInitialAlignment
 KFPCSInitialAlignment computes corresponding four point congruent sets based on keypoints as described in: "Markerless point cloud registration with keypoint-based 4-points congruent sets", Pascal Theiler, Jan Dirk Wegner, Konrad Schindler. More...
 
class  LUM
 Globally Consistent Scan Matching based on an algorithm by Lu and Milios. More...
 
struct  MatchingCandidate
 Container for matching candidate consisting of. More...
 
class  MetaRegistration
 Meta Registration class. More...
 
struct  NullEstimate
 NullEstimate struct More...
 
struct  NullMeasurement
 NullMeasurement struct More...
 
struct  PoseEstimate
 PoseEstimate struct More...
 
struct  PoseMeasurement
 PoseMeasurement struct More...
 
struct  sortCorrespondencesByDistance
 sortCorrespondencesByDistance : a functor for sorting correspondences by distance More...
 
struct  sortCorrespondencesByMatchIndex
 sortCorrespondencesByMatchIndex : a functor for sorting correspondences by match index More...
 
struct  sortCorrespondencesByMatchIndexAndDistance
 sortCorrespondencesByMatchIndexAndDistance : a functor for sorting correspondences by match index and distance More...
 
struct  sortCorrespondencesByQueryIndex
 sortCorrespondencesByQueryIndex : a functor for sorting correspondences by query index More...
 
struct  sortCorrespondencesByQueryIndexAndDistance
 sortCorrespondencesByQueryIndexAndDistance : a functor for sorting correspondences by query index and distance More...
 
class  TransformationEstimation
 TransformationEstimation represents the base class for methods for transformation estimation based on: More...
 
class  TransformationEstimation2D
 TransformationEstimation2D implements a simple 2D rigid transformation estimation (x, y, theta) for a given pair of datasets. More...
 
class  TransformationEstimation3Point
 TransformationEstimation3Points represents the class for transformation estimation based on: More...
 
class  TransformationEstimationDQ
 TransformationEstimationDQ implements dual quaternion based estimation of the transformation aligning the given correspondences. More...
 
class  TransformationEstimationDualQuaternion
 TransformationEstimationDualQuaternion implements dual quaternion based estimation of the transformation aligning the given correspondences. More...
 
class  TransformationEstimationLM
 TransformationEstimationLM implements Levenberg Marquardt-based estimation of the transformation aligning the given correspondences. More...
 
class  TransformationEstimationPointToPlane
 TransformationEstimationPointToPlane uses Levenberg Marquardt optimization to find the transformation that minimizes the point-to-plane distance between the given correspondences. More...
 
class  TransformationEstimationPointToPlaneLLS
 TransformationEstimationPointToPlaneLLS implements a Linear Least Squares (LLS) approximation for minimizing the point-to-plane distance between two clouds of corresponding points with normals. More...
 
class  TransformationEstimationPointToPlaneLLSWeighted
 TransformationEstimationPointToPlaneLLSWeighted implements a Linear Least Squares (LLS) approximation for minimizing the point-to-plane distance between two clouds of corresponding points with normals, with the possibility of assigning weights to the correspondences. More...
 
class  TransformationEstimationPointToPlaneWeighted
 TransformationEstimationPointToPlaneWeighted uses Levenberg Marquardt optimization to find the transformation that minimizes the point-to-plane distance between the given correspondences. More...
 
class  TransformationEstimationSVD
 TransformationEstimationSVD implements SVD-based estimation of the transformation aligning the given correspondences. More...
 
class  TransformationEstimationSVDScale
 TransformationEstimationSVD implements SVD-based estimation of the transformation aligning the given correspondences. More...
 
class  TransformationValidation
 TransformationValidation represents the base class for methods that validate the correctness of a transformation found through TransformationEstimation. More...
 
class  TransformationValidationEuclidean
 TransformationValidationEuclidean computes an L2SQR norm between a source and target dataset. More...
 
class  WarpPointRigid
 Base warp point class. More...
 
class  WarpPointRigid3D
 WarpPointRigid3D enables 3D (1D rotation + 2D translation) transformations for points. More...
 
class  WarpPointRigid6D
 WarpPointRigid3D enables 6D (3D rotation + 3D translation) transformations for points. More...
 

Typedefs

typedef std::vector< MatchingCandidate, Eigen::aligned_allocator< MatchingCandidate > > MatchingCandidates
 

Functions

void getCorDistMeanStd (const pcl::Correspondences &correspondences, double &mean, double &stddev)
 calculates the mean and standard deviation of descriptor distances from correspondences More...
 
void getQueryIndices (const pcl::Correspondences &correspondences, std::vector< int > &indices)
 extracts the query indices More...
 
void getMatchIndices (const pcl::Correspondences &correspondences, std::vector< int > &indices)
 extracts the match indices More...
 

Typedef Documentation

typedef std::vector<MatchingCandidate, Eigen::aligned_allocator<MatchingCandidate> > pcl::registration::MatchingCandidates

Definition at line 88 of file matching_candidate.h.

Function Documentation

void pcl::registration::getCorDistMeanStd ( const pcl::Correspondences correspondences,
double &  mean,
double &  stddev 
)
inline

calculates the mean and standard deviation of descriptor distances from correspondences

Parameters
[in]correspondenceslist of correspondences
[out]meanthe mean descriptor distance of correspondences
[out]stddevthe standard deviation of descriptor distances.
Note
The sample variance is used to determine the standard deviation

Definition at line 48 of file correspondence_types.hpp.

void pcl::registration::getMatchIndices ( const pcl::Correspondences correspondences,
std::vector< int > &  indices 
)
inline

extracts the match indices

Parameters
[in]correspondenceslist of correspondences
[out]indicesarray of extracted indices.
Note
order of indices corresponds to input list of descriptor correspondences

Definition at line 76 of file correspondence_types.hpp.

void pcl::registration::getQueryIndices ( const pcl::Correspondences correspondences,
std::vector< int > &  indices 
)
inline

extracts the query indices

Parameters
[in]correspondenceslist of correspondences
[out]indicesarray of extracted indices.
Note
order of indices corresponds to input list of descriptor correspondences

Definition at line 67 of file correspondence_types.hpp.