GeneralizedIterativeClosestPoint6D integrates L*a*b* color space information into the Generalized Iterative Closest Point (GICP) algorithm. More...
#include <pcl/registration/gicp6d.h>
Classes |
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| class | MyPointRepresentation |
| Custom point representation to perform kdtree searches in more than 3 (i.e. More... |
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Public Member Functions |
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| GeneralizedIterativeClosestPoint6D (float lab_weight=0.032f) | |
| constructor. More... |
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| void | setInputSource (const PointCloudSourceConstPtr &cloud) override |
| Provide a pointer to the input source (e.g., the point cloud that we want to align to the target) More... |
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| void | setInputTarget (const PointCloudTargetConstPtr &target) override |
| Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to) More... |
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 Public Member Functions inherited from pcl::GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA > |
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| GeneralizedIterativeClosestPoint () | |
| Empty constructor. More... |
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| void | setInputSource (const PointCloudSourceConstPtr &cloud) override |
| Provide a pointer to the input dataset. More... |
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| void | setSourceCovariances (const MatricesVectorPtr &covariances) |
| Provide a pointer to the covariances of the input source (if computed externally!). More... |
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| void | setInputTarget (const PointCloudTargetConstPtr &target) override |
| Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to) More... |
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| void | setTargetCovariances (const MatricesVectorPtr &covariances) |
| Provide a pointer to the covariances of the input target (if computed externally!). More... |
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| void | estimateRigidTransformationBFGS (const PointCloudSource &cloud_src, const pcl::Indices &indices_src, const PointCloudTarget &cloud_tgt, const pcl::Indices &indices_tgt, Eigen::Matrix4f &transformation_matrix) |
| Estimate a rigid rotation transformation between a source and a target point cloud using an iterative non-linear Levenberg-Marquardt approach. More... |
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| const Eigen::Matrix3d & | mahalanobis (std::size_t index) const |
| void | computeRDerivative (const Vector6d &x, const Eigen::Matrix3d &R, Vector6d &g) const |
| Computes rotation matrix derivative. More... |
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| void | setRotationEpsilon (double epsilon) |
| Set the rotation epsilon (maximum allowable difference between two consecutive rotations) in order for an optimization to be considered as having converged to the final solution. More... |
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| double | getRotationEpsilon () const |
| Get the rotation epsilon (maximum allowable difference between two consecutive rotations) as set by the user. More... |
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| void | setCorrespondenceRandomness (int k) |
| Set the number of neighbors used when selecting a point neighbourhood to compute covariances. More... |
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| int | getCorrespondenceRandomness () const |
| Get the number of neighbors used when computing covariances as set by the user. More... |
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| void | setMaximumOptimizerIterations (int max) |
| Set maximum number of iterations at the optimization step. More... |
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| int | getMaximumOptimizerIterations () const |
| Return maximum number of iterations at the optimization step. More... |
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| void | setTranslationGradientTolerance (double tolerance) |
| Set the minimal translation gradient threshold for early optimization stop. More... |
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| double | getTranslationGradientTolerance () const |
| Return the minimal translation gradient threshold for early optimization stop. More... |
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| void | setRotationGradientTolerance (double tolerance) |
| Set the minimal rotation gradient threshold for early optimization stop. More... |
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| double | getRotationGradientTolerance () const |
| Return the minimal rotation gradient threshold for early optimization stop. More... |
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| Public Member Functions inherited from pcl::IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA > |
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| IterativeClosestPoint () | |
| Empty constructor. More... |
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| IterativeClosestPoint (const IterativeClosestPoint &)=delete | |
Due to convergence_criteria_ holding references to the class members, it is tricky to correctly implement its copy and move operations correctly. More... |
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| IterativeClosestPoint (IterativeClosestPoint &&)=delete | |
| IterativeClosestPoint & | operator= (const IterativeClosestPoint &)=delete |
| IterativeClosestPoint & | operator= (IterativeClosestPoint &&)=delete |
| ~IterativeClosestPoint () | |
| Empty destructor. More... |
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| pcl::registration::DefaultConvergenceCriteria< float >::Ptr | getConvergeCriteria () |
| Returns a pointer to the DefaultConvergenceCriteria used by the IterativeClosestPoint class. More... |
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| void | setInputSource (const PointCloudSourceConstPtr &cloud) override |
| Provide a pointer to the input source (e.g., the point cloud that we want to align to the target) More... |
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| void | setInputTarget (const PointCloudTargetConstPtr &cloud) override |
| Provide a pointer to the input target (e.g., the point cloud that we want to align to the target) More... |
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| void | setUseReciprocalCorrespondences (bool use_reciprocal_correspondence) |
| Set whether to use reciprocal correspondence or not. More... |
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| bool | getUseReciprocalCorrespondences () const |
| Obtain whether reciprocal correspondence are used or not. More... |
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| Public Member Functions inherited from pcl::Registration< PointXYZRGBA, PointXYZRGBA, float > |
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| Registration () | |
| Empty constructor. More... |
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| ~Registration () | |
| destructor. More... |
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| void | setTransformationEstimation (const TransformationEstimationPtr &te) |
| Provide a pointer to the transformation estimation object. More... |
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| void | setCorrespondenceEstimation (const CorrespondenceEstimationPtr &ce) |
| Provide a pointer to the correspondence estimation object. More... |
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| const PointCloudSourceConstPtr | getInputSource () |
| Get a pointer to the input point cloud dataset target. More... |
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| const PointCloudTargetConstPtr | getInputTarget () |
| Get a pointer to the input point cloud dataset target. More... |
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| 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... |
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| KdTreePtr | getSearchMethodTarget () const |
| Get a pointer to the search method used to find correspondences in the target cloud. More... |
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| 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... |
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| KdTreeReciprocalPtr | getSearchMethodSource () const |
| Get a pointer to the search method used to find correspondences in the source cloud. More... |
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| Matrix4 | getFinalTransformation () |
| Get the final transformation matrix estimated by the registration method. More... |
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| Matrix4 | getLastIncrementalTransformation () |
| Get the last incremental transformation matrix estimated by the registration method. More... |
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| void | setMaximumIterations (int nr_iterations) |
| Set the maximum number of iterations the internal optimization should run for. More... |
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| int | getMaximumIterations () |
| Get the maximum number of iterations the internal optimization should run for, as set by the user. More... |
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| void | setRANSACIterations (int ransac_iterations) |
| Set the number of iterations RANSAC should run for. More... |
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| double | getRANSACIterations () |
| Get the number of iterations RANSAC should run for, as set by the user. More... |
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| void | setRANSACOutlierRejectionThreshold (double inlier_threshold) |
| Set the inlier distance threshold for the internal RANSAC outlier rejection loop. More... |
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| double | getRANSACOutlierRejectionThreshold () |
| Get the inlier distance threshold for the internal outlier rejection loop as set by the user. More... |
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| void | setMaxCorrespondenceDistance (double distance_threshold) |
| Set the maximum distance threshold between two correspondent points in source <-> target. More... |
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| double | getMaxCorrespondenceDistance () |
| Get the maximum distance threshold between two correspondent points in source <-> target. More... |
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| 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... |
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| double | getTransformationEpsilon () |
| Get the transformation epsilon (maximum allowable translation squared difference between two consecutive transformations) as set by the user. More... |
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| 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... |
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| 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... |
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| 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... |
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| double | getEuclideanFitnessEpsilon () |
| Get the maximum allowed distance error before the algorithm will be considered to have converged, as set by the user. More... |
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| void | setPointRepresentation (const PointRepresentationConstPtr &point_representation) |
| Provide a boost shared pointer to the PointRepresentation to be used when comparing points. More... |
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| bool | registerVisualizationCallback (std::function< UpdateVisualizerCallbackSignature > &visualizerCallback) |
| Register the user callback function which will be called from registration thread in order to update point cloud obtained after each iteration. More... |
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| double | getFitnessScore (double max_range=std::numeric_limits< double >::max()) |
| Obtain the Euclidean fitness score (e.g., mean of squared distances from the source to the target) More... |
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| double | getFitnessScore (const std::vector< float > &distances_a, const std::vector< float > &distances_b) |
| Obtain the Euclidean fitness score (e.g., mean of squared distances from the source to the target) from two sets of correspondence distances (distances between source and target points) More... |
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| bool | hasConverged () const |
| Return the state of convergence after the last align run. More... |
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| void | align (PointCloudSource &output) |
| Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output. More... |
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| void | align (PointCloudSource &output, const Matrix4 &guess) |
| Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output. More... |
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| const std::string & | getClassName () const |
| Abstract class get name method. More... |
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| bool | initCompute () |
| Internal computation initialization. More... |
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| bool | initComputeReciprocal () |
| Internal computation when reciprocal lookup is needed. More... |
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| void | addCorrespondenceRejector (const CorrespondenceRejectorPtr &rejector) |
| Add a new correspondence rejector to the list. More... |
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| std::vector< CorrespondenceRejectorPtr > | getCorrespondenceRejectors () |
| Get the list of correspondence rejectors. More... |
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| bool | removeCorrespondenceRejector (unsigned int i) |
| Remove the i-th correspondence rejector in the list. More... |
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| void | clearCorrespondenceRejectors () |
| Clear the list of correspondence rejectors. More... |
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| Public Member Functions inherited from pcl::PCLBase< PointXYZRGBA > |
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| PCLBase () | |
| Empty constructor. More... |
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| PCLBase (const PCLBase &base) | |
| Copy constructor. More... |
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| virtual | ~PCLBase ()=default |
| Destructor. More... |
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| virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
| Provide a pointer to the input dataset. More... |
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| const PointCloudConstPtr | getInputCloud () const |
| Get a pointer to the input point cloud dataset. More... |
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| virtual void | setIndices (const IndicesPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (const IndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (const PointIndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols) |
| Set the indices for the points laying within an interest region of the point cloud. More... |
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| IndicesPtr | getIndices () |
| Get a pointer to the vector of indices used. More... |
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| const IndicesConstPtr | getIndices () const |
| Get a pointer to the vector of indices used. More... |
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| const PointXYZRGBA & | operator[] (std::size_t pos) const |
| Override PointCloud operator[] to shorten code. More... |
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Protected Member Functions |
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| void | computeTransformation (PointCloudSource &output, const Eigen::Matrix4f &guess) override |
| Rigid transformation computation method with initial guess. More... |
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| bool | searchForNeighbors (const PointXYZLAB &query, pcl::Indices &index, std::vector< float > &distance) |
| Search for the closest nearest neighbor of a given point. More... |
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| Protected Member Functions inherited from pcl::GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA > |
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| void | computeCovariances (typename pcl::PointCloud< PointT >::ConstPtr cloud, const typename pcl::search::KdTree< PointT >::Ptr tree, MatricesVector &cloud_covariances) |
| compute points covariances matrices according to the K nearest neighbors. More... |
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| double | matricesInnerProd (const Eigen::MatrixXd &mat1, const Eigen::MatrixXd &mat2) const |
| void | computeTransformation (PointCloudSource &output, const Eigen::Matrix4f &guess) override |
| Rigid transformation computation method with initial guess. More... |
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| bool | searchForNeighbors (const PointXYZRGBA &query, pcl::Indices &index, std::vector< float > &distance) |
| Search for the closest nearest neighbor of a given point. More... |
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| void | applyState (Eigen::Matrix4f &t, const Vector6d &x) const |
| compute transformation matrix from transformation matrix More... |
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| Protected Member Functions inherited from pcl::IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA > |
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| virtual void | transformCloud (const PointCloudSource &input, PointCloudSource &output, const Matrix4 &transform) |
| Apply a rigid transform to a given dataset. More... |
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| void | computeTransformation (PointCloudSource &output, const Matrix4 &guess) override |
| Rigid transformation computation method with initial guess. More... |
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| virtual void | determineRequiredBlobData () |
| Looks at the Estimators and Rejectors and determines whether their blob-setter methods need to be called. More... |
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| Protected Member Functions inherited from pcl::Registration< PointXYZRGBA, PointXYZRGBA, float > |
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| bool | searchForNeighbors (const PointCloudSource &cloud, int index, pcl::Indices &indices, std::vector< float > &distances) |
| Search for the closest nearest neighbor of a given point. More... |
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| virtual void | computeTransformation (PointCloudSource &output, const Matrix4 &guess)=0 |
| Abstract transformation computation method with initial guess. More... |
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| Protected Member Functions inherited from pcl::PCLBase< PointXYZRGBA > |
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| bool | initCompute () |
| This method should get called before starting the actual computation. More... |
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| bool | deinitCompute () |
| This method should get called after finishing the actual computation. More... |
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Protected Attributes |
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| pcl::PointCloud< PointXYZLAB >::Ptr | cloud_lab_ |
| Holds the converted (LAB) data cloud. More... |
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| pcl::PointCloud< PointXYZLAB >::Ptr | target_lab_ |
| Holds the converted (LAB) model cloud. More... |
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| KdTreeFLANN< PointXYZLAB > | target_tree_lab_ |
| 6d-tree to search in model cloud. More... |
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| float | lab_weight_ |
| The color weight. More... |
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| MyPointRepresentation | point_rep_ |
| Enables 6d searches with kd-tree class using the color weight. More... |
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| Protected Attributes inherited from pcl::GeneralizedIterativeClosestPoint< PointXYZRGBA, PointXYZRGBA > |
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| int | k_correspondences_ |
| The number of neighbors used for covariances computation. More... |
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| double | gicp_epsilon_ |
| The epsilon constant for gicp paper; this is NOT the convergence tolerance default: 0.001. More... |
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| double | rotation_epsilon_ |
| The epsilon constant for rotation error. More... |
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| Eigen::Matrix4f | base_transformation_ |
| base transformation More... |
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| const PointCloudSource * | tmp_src_ |
| Temporary pointer to the source dataset. More... |
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| const PointCloudTarget * | tmp_tgt_ |
| Temporary pointer to the target dataset. More... |
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| const pcl::Indices * | tmp_idx_src_ |
| Temporary pointer to the source dataset indices. More... |
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| const pcl::Indices * | tmp_idx_tgt_ |
| Temporary pointer to the target dataset indices. More... |
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| MatricesVectorPtr | input_covariances_ |
| Input cloud points covariances. More... |
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| MatricesVectorPtr | target_covariances_ |
| Target cloud points covariances. More... |
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| std::vector< Eigen::Matrix3d > | mahalanobis_ |
| Mahalanobis matrices holder. More... |
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| int | max_inner_iterations_ |
| maximum number of optimizations More... |
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| double | translation_gradient_tolerance_ |
| minimal translation gradient for early optimization stop More... |
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| double | rotation_gradient_tolerance_ |
| minimal rotation gradient for early optimization stop More... |
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| std::function< void(const pcl::PointCloud< PointXYZRGBA > &cloud_src, const pcl::Indices &src_indices, const pcl::PointCloud< PointXYZRGBA > &cloud_tgt, const pcl::Indices &tgt_indices, Eigen::Matrix4f &transformation_matrix)> | rigid_transformation_estimation_ |
| Protected Attributes inherited from pcl::IterativeClosestPoint< PointXYZRGBA, PointXYZRGBA > |
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| std::size_t | x_idx_offset_ |
| XYZ fields offset. More... |
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| std::size_t | y_idx_offset_ |
| std::size_t | z_idx_offset_ |
| std::size_t | nx_idx_offset_ |
| Normal fields offset. More... |
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| std::size_t | ny_idx_offset_ |
| std::size_t | nz_idx_offset_ |
| bool | use_reciprocal_correspondence_ |
| The correspondence type used for correspondence estimation. More... |
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| bool | source_has_normals_ |
| Internal check whether source dataset has normals or not. More... |
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| bool | target_has_normals_ |
| Internal check whether target dataset has normals or not. More... |
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| bool | need_source_blob_ |
| Checks for whether estimators and rejectors need various data. More... |
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| bool | need_target_blob_ |
| Protected Attributes inherited from pcl::Registration< PointXYZRGBA, PointXYZRGBA, float > |
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| std::string | reg_name_ |
| The registration method name. More... |
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| KdTreePtr | tree_ |
| A pointer to the spatial search object. More... |
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| KdTreeReciprocalPtr | tree_reciprocal_ |
| A pointer to the spatial search object of the source. More... |
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| int | nr_iterations_ |
| The number of iterations the internal optimization ran for (used internally). More... |
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| int | max_iterations_ |
| The maximum number of iterations the internal optimization should run for. More... |
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| int | ransac_iterations_ |
| The number of iterations RANSAC should run for. More... |
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| PointCloudTargetConstPtr | target_ |
| The input point cloud dataset target. More... |
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| Matrix4 | final_transformation_ |
| The final transformation matrix estimated by the registration method after N iterations. More... |
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| Matrix4 | transformation_ |
| The transformation matrix estimated by the registration method. More... |
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| Matrix4 | previous_transformation_ |
| The previous transformation matrix estimated by the registration method (used internally). More... |
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| double | transformation_epsilon_ |
| The maximum difference between two consecutive transformations in order to consider convergence (user defined). More... |
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| double | transformation_rotation_epsilon_ |
| The maximum rotation difference between two consecutive transformations in order to consider convergence (user defined). More... |
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| 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... |
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| double | corr_dist_threshold_ |
| The maximum distance threshold between two correspondent points in source <-> target. More... |
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| double | inlier_threshold_ |
| The inlier distance threshold for the internal RANSAC outlier rejection loop. More... |
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| bool | converged_ |
| Holds internal convergence state, given user parameters. More... |
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| int | min_number_correspondences_ |
| The minimum number of correspondences that the algorithm needs before attempting to estimate the transformation. More... |
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| CorrespondencesPtr | correspondences_ |
| The set of correspondences determined at this ICP step. More... |
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| TransformationEstimationPtr | transformation_estimation_ |
| A TransformationEstimation object, used to calculate the 4x4 rigid transformation. More... |
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| CorrespondenceEstimationPtr | correspondence_estimation_ |
| A CorrespondenceEstimation object, used to estimate correspondences between the source and the target cloud. More... |
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| std::vector< CorrespondenceRejectorPtr > | correspondence_rejectors_ |
| The list of correspondence rejectors to use. More... |
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| bool | target_cloud_updated_ |
| Variable that stores whether we have a new target cloud, meaning we need to pre-process it again. More... |
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| bool | source_cloud_updated_ |
| Variable that stores whether we have a new source cloud, meaning we need to pre-process it again. More... |
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| bool | force_no_recompute_ |
| A flag which, if set, means the tree operating on the target cloud will never be recomputed. More... |
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| bool | force_no_recompute_reciprocal_ |
| A flag which, if set, means the tree operating on the source cloud will never be recomputed. More... |
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| std::function< UpdateVisualizerCallbackSignature > | update_visualizer_ |
| Callback function to update intermediate source point cloud position during it's registration to the target point cloud. More... |
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| Protected Attributes inherited from pcl::PCLBase< PointXYZRGBA > |
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| PointCloudConstPtr | input_ |
| The input point cloud dataset. More... |
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| IndicesPtr | indices_ |
| A pointer to the vector of point indices to use. More... |
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| bool | use_indices_ |
| Set to true if point indices are used. More... |
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| bool | fake_indices_ |
| If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More... |
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Detailed Description
GeneralizedIterativeClosestPoint6D integrates L*a*b* color space information into the Generalized Iterative Closest Point (GICP) algorithm.
The suggested input is PointXYZRGBA.
- Note
- If you use this code in any academic work, please cite:
- M. Korn, M. Holzkothen, J. Pauli Color Supported Generalized-ICP. In Proceedings of VISAPP 2014 - International Conference on Computer Vision Theory and Applications, Lisbon, Portugal, January 2014.
Constructor & Destructor Documentation
GeneralizedIterativeClosestPoint6D()
| pcl::GeneralizedIterativeClosestPoint6D::GeneralizedIterativeClosestPoint6D | ( | float | lab_weight = 0.032f |
) |
constructor.
- Parameters
-
[in] lab_weight the color weight
Member Function Documentation
computeTransformation()
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overrideprotected |
Rigid transformation computation method with initial guess.
- Parameters
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output the transformed input point cloud dataset using the rigid transformation found guess the initial guess of the transformation to compute
searchForNeighbors()
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inlineprotected |
Search for the closest nearest neighbor of a given point.
- Parameters
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query the point to search a nearest neighbour for index vector of size 1 to store the index of the nearest neighbour found distance vector of size 1 to store the distance to nearest neighbour found
setInputSource()
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overridevirtual |
Provide a pointer to the input source (e.g., the point cloud that we want to align to the target)
- Parameters
-
[in] cloud the input point cloud source
Reimplemented from pcl::Registration< PointXYZRGBA, PointXYZRGBA, float >.
setInputTarget()
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overridevirtual |
Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to)
- Parameters
-
[in] target the input point cloud target
Reimplemented from pcl::Registration< PointXYZRGBA, PointXYZRGBA, float >.
Member Data Documentation
cloud_lab_
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protected |
lab_weight_
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protected |
point_rep_
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protected |
target_lab_
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protected |
target_tree_lab_
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protected |
The documentation for this class was generated from the following file:
- pcl/registration/gicp6d.h
© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_generalized_iterative_closest_point6_d.html
