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>
Public Member Functions |
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| FPCSInitialAlignment () | |
| Constructor. More... |
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| ~FPCSInitialAlignment () | |
| Destructor. More... |
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| void | setTargetIndices (const IndicesPtr &target_indices) |
| Provide a pointer to the vector of target indices. More... |
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| IndicesPtr | getTargetIndices () const |
| void | setSourceNormals (const NormalsConstPtr &source_normals) |
| Provide a pointer to the normals of the source point cloud. More... |
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| NormalsConstPtr | getSourceNormals () const |
| void | setTargetNormals (const NormalsConstPtr &target_normals) |
| Provide a pointer to the normals of the target point cloud. More... |
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| NormalsConstPtr | getTargetNormals () const |
| void | setNumberOfThreads (int nr_threads) |
| Set the number of used threads if OpenMP is activated. More... |
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| int | getNumberOfThreads () const |
| void | setDelta (float delta, bool normalize=false) |
| Set the constant factor delta which weights the internally calculated parameters. More... |
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| float | getDelta () const |
| void | setApproxOverlap (float approx_overlap) |
| Set the approximate overlap between source and target. More... |
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| float | getApproxOverlap () const |
| void | setScoreThreshold (float score_threshold) |
| Set the scoring threshold used for early finishing the method. More... |
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| float | getScoreThreshold () const |
| void | setNumberOfSamples (int nr_samples) |
| Set the number of source samples to use during alignment. More... |
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| int | getNumberOfSamples () const |
| void | setMaxNormalDifference (float max_norm_diff) |
| Set the maximum normal difference between valid point correspondences in degree. More... |
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| float | getMaxNormalDifference () const |
| void | setMaxComputationTime (int max_runtime) |
| Set the maximum computation time in seconds. More... |
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| int | getMaxComputationTime () const |
| float | getFitnessScore () const |
 Public Member Functions inherited from pcl::Registration< PointSource, PointTarget, 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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| 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... |
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| const PointCloudSourceConstPtr | getInputSource () |
| Get a pointer to the input point cloud dataset target. More... |
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| 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... |
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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< PointSource > |
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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 PointSource & | 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. More... |
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| virtual bool | initCompute () |
| Internal computation initialization. More... |
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| int | selectBase (pcl::Indices &base_indices, float(&ratio)[2]) |
| Select an approximately coplanar set of four points from the source cloud. More... |
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| int | selectBaseTriangle (pcl::Indices &base_indices) |
| Select randomly a triplet of points with large point-to-point distances. More... |
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| void | setupBase (pcl::Indices &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... |
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| float | segmentToSegmentDist (const pcl::Indices &base_indices, float(&ratio)[2]) |
| Calculate intersection ratios and segment to segment distances of base diagonals. More... |
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| virtual int | bruteForceCorrespondences (int idx1, int idx2, pcl::Correspondences &pairs) |
| Search for corresponding point pairs given the distance between two base points. More... |
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| virtual int | determineBaseMatches (const pcl::Indices &base_indices, std::vector< pcl::Indices > &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... |
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| int | checkBaseMatch (const pcl::Indices &match_indices, const float(&ds)[4]) |
| Check if outer rectangle distance of matched points fit with the base rectangle. More... |
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| virtual void | handleMatches (const pcl::Indices &base_indices, std::vector< pcl::Indices > &matches, MatchingCandidates &candidates) |
| Method to handle current candidate matches. More... |
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| virtual void | linkMatchWithBase (const pcl::Indices &base_indices, pcl::Indices &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... |
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| virtual int | validateMatch (const pcl::Indices &base_indices, const pcl::Indices &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... |
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| virtual int | validateTransformation (Eigen::Matrix4f &transformation, float &fitness_score) |
| Validate the transformation by calculating the number of inliers after transforming the source cloud. More... |
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| virtual void | finalCompute (const std::vector< MatchingCandidates > &candidates) |
| Final computation of best match out of vector of best matches. More... |
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| Protected Member Functions inherited from pcl::Registration< PointSource, PointTarget, 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< PointSource > |
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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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| NormalsConstPtr | source_normals_ |
| Normals of source point cloud. More... |
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| NormalsConstPtr | target_normals_ |
| Normals of target point cloud. More... |
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| int | nr_threads_ |
| Number of threads for parallelization (standard = 1). More... |
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| float | approx_overlap_ |
| Estimated overlap between source and target (standard = 0.5). More... |
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| float | delta_ |
| Delta value of 4pcs algorithm (standard = 1.0). More... |
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| float | score_threshold_ |
| Score threshold to stop calculation with success. More... |
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| int | nr_samples_ |
| The number of points to uniformly sample the source point cloud. More... |
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| float | max_norm_diff_ |
| Maximum normal difference of corresponding point pairs in degrees (standard = 90). More... |
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| int | max_runtime_ |
| Maximum allowed computation time in seconds (standard = 0 => ~unlimited). More... |
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| float | fitness_score_ |
| Resulting fitness score of the best match. More... |
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| float | diameter_ |
| Estimated diamter of the target point cloud. More... |
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| float | max_base_diameter_sqr_ |
| Estimated squared metric overlap between source and target. More... |
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| bool | use_normals_ |
| Use normals flag. More... |
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| bool | normalize_delta_ |
| Normalize delta flag. More... |
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| pcl::IndicesPtr | source_indices_ |
| A pointer to the vector of source point indices to use after sampling. More... |
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| pcl::IndicesPtr | target_indices_ |
| A pointer to the vector of target point indices to use after sampling. More... |
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| float | max_pair_diff_ |
| Maximal difference between corresponding point pairs in source and target. More... |
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| float | max_edge_diff_ |
| Maximal difference between the length of the base edges and valid match edges. More... |
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| float | coincidation_limit_ |
| Maximal distance between coinciding intersection points to find valid matches. More... |
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| float | max_mse_ |
| Maximal mean squared errors of a transformation calculated from a candidate match. More... |
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| float | max_inlier_dist_sqr_ |
| Maximal squared point distance between source and target points to count as inlier. More... |
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| const float | small_error_ |
| Definition of a small error. More... |
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| Protected Attributes inherited from pcl::Registration< PointSource, PointTarget, 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< PointSource > |
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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
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
Constructor & Destructor Documentation
FPCSInitialAlignment()
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 134 of file ia_fpcs.hpp.
~FPCSInitialAlignment()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
Member Function Documentation
bruteForceCorrespondences()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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protectedvirtual |
Search for corresponding point pairs given the distance between two base points.
- Parameters
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[in] idx1 first index of current base segment (in source cloud) [in] idx2 second index of current base segment (in source cloud) [out] pairs resulting point pairs with point-to-point distance close to ref_dist
- Returns
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- < 0 no corresponding point pair was found
- = 0 at least one point pair candidate was found
Definition at line 579 of file ia_fpcs.hpp.
checkBaseMatch()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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protected |
Check if outer rectangle distance of matched points fit with the base rectangle.
- Parameters
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[in] match_indices indices of match M [in] ds edge lengths of base B
- Returns
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- < 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 715 of file ia_fpcs.hpp.
computeTransformation()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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overrideprotected |
Rigid transformation computation method.
- Parameters
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output the transformed input point cloud dataset using the rigid transformation found guess The computed transforamtion
Definition at line 167 of file ia_fpcs.hpp.
determineBaseMatches()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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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
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[in] base_indices indices of base B [out] matches vector of candidate matches w.r.t the base B [in] pairs_a point pairs corresponding to points of 1st diagonal of base B [in] pairs_b point pairs corresponding to points of 2nd diagonal of base B [in] ratio diagonal intersection ratios of base points
- Returns
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- < 0 no base match could be found
- = 0 at least one base match was found
Definition at line 633 of file ia_fpcs.hpp.
finalCompute()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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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
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[in] candidates vector of candidate matches
Reimplemented in pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >.
Definition at line 904 of file ia_fpcs.hpp.
getApproxOverlap()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
getDelta()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
getFitnessScore()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
getMaxComputationTime()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
getMaxNormalDifference()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
getNumberOfSamples()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
getNumberOfThreads()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
getScoreThreshold()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
getSourceNormals()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
getTargetIndices()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
getTargetNormals()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
handleMatches()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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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
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[in] base_indices indices of base B [in,out] matches vector of candidate matches w.r.t the base B. The candidate matches are reordered during this step. [out] candidates vector which contains the candidates matches M
Reimplemented in pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >.
Definition at line 739 of file ia_fpcs.hpp.
initCompute()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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protectedvirtual |
Internal computation initialization.
Reimplemented in pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >.
Definition at line 240 of file ia_fpcs.hpp.
Referenced by pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::initCompute().
linkMatchWithBase()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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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
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[in] base_indices indices of base B [in] match_indices indices of match M [out] correspondences resulting correspondences
Definition at line 777 of file ia_fpcs.hpp.
segmentToSegmentDist()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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protected |
Calculate intersection ratios and segment to segment distances of base diagonals.
- Parameters
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[in] base_indices indices of base B [out] ratio diagonal intersection ratios of base points
- Returns
- quality value of diagonal intersection
Definition at line 494 of file ia_fpcs.hpp.
selectBase()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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protected |
Select an approximately coplanar set of four points from the source cloud.
- Parameters
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[out] base_indices selected source cloud indices, further used as base (B) [out] ratio the two diagonal intersection ratios (r1,r2) of the base points
- Returns
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- < 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 347 of file ia_fpcs.hpp.
selectBaseTriangle()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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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
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[out] base_indices indices of base B
- Returns
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- < 0 no triangle with large enough base lines could be selected
- = 0 base triangle succesully selected
Definition at line 413 of file ia_fpcs.hpp.
setApproxOverlap()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
setDelta()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
setMaxComputationTime()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
setMaxNormalDifference()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
setNumberOfSamples()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
setNumberOfThreads()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
setScoreThreshold()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
setSourceNormals()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
setTargetIndices()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
setTargetNormals()
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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inline |
setupBase()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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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_indices indices of base B (will be reordered) [out] ratio diagonal intersection ratios of base points
Definition at line 451 of file ia_fpcs.hpp.
validateMatch()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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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_indices indices of base B [in] match_indices indices of match M [in] correspondences corresondences between source and target [out] transformation resulting transformation matrix
- Returns
-
- < 0 MSE bigger than max_mse_
- = 0 MSE smaller than max_mse_
Definition at line 830 of file ia_fpcs.hpp.
validateTransformation()
template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >
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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] transformation updated orientation matrix using all inliers [out] fitness_score current 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 862 of file ia_fpcs.hpp.
Member Data Documentation
approx_overlap_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
Estimated overlap between source and target (standard = 0.5).
Definition at line 476 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getApproxOverlap(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setApproxOverlap().
coincidation_limit_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
delta_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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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 485 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getDelta(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setDelta().
diameter_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
fitness_score_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
Resulting fitness score of the best match.
Definition at line 505 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getFitnessScore().
max_base_diameter_sqr_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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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 tries to reliably find a correct match.
max_edge_diff_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
max_inlier_dist_sqr_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
max_mse_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
max_norm_diff_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
Maximum normal difference of corresponding point pairs in degrees (standard = 90).
Definition at line 498 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getMaxNormalDifference(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setMaxNormalDifference().
max_pair_diff_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
max_runtime_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
Maximum allowed computation time in seconds (standard = 0 => ~unlimited).
Definition at line 502 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getMaxComputationTime(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setMaxComputationTime().
normalize_delta_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
Normalize delta flag.
Definition at line 521 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setDelta().
nr_samples_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
The number of points to uniformly sample the source point cloud.
(standard = 0 => full cloud).
Definition at line 494 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getNumberOfSamples(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setNumberOfSamples().
nr_threads_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
Number of threads for parallelization (standard = 1).
- Note
- Only used if run compiled with OpenMP.
Definition at line 473 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getNumberOfThreads(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setNumberOfThreads().
score_threshold_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
Score threshold to stop calculation with success.
If not set by the user it depends on the size of the approximated overlap
Definition at line 490 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getScoreThreshold(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setScoreThreshold().
small_error_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
source_indices_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
source_normals_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
Normals of source point cloud.
Definition at line 465 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getSourceNormals(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setSourceNormals().
target_indices_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
A pointer to the vector of target point indices to use after sampling.
Definition at line 527 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getTargetIndices(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setTargetIndices().
target_normals_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
Normals of target point cloud.
Definition at line 468 of file ia_fpcs.h.
Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::getTargetNormals(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::setTargetNormals().
use_normals_
template<typename PointSource , typename PointTarget , typename NormalT = pcl::Normal, typename Scalar = float>
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protected |
The documentation for this class was generated from the following files:
- pcl/registration/ia_fpcs.h
- pcl/registration/impl/ia_fpcs.hpp
© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html
