Open3D (C++ API)
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Data Structures | |
class | CorrespondenceChecker |
class | CorrespondenceCheckerBasedOnDistance |
Check if two aligned point clouds are close. More... | |
class | CorrespondenceCheckerBasedOnEdgeLength |
class | CorrespondenceCheckerBasedOnNormal |
Check if two aligned point clouds have similar normals. More... | |
class | FastGlobalRegistrationOption |
class | Feature |
class | GlobalOptimizationConvergenceCriteria |
class | GlobalOptimizationGaussNewton |
class | GlobalOptimizationLevenbergMarquardt |
class | GlobalOptimizationMethod |
class | GlobalOptimizationOption |
class | ICPConvergenceCriteria |
class | PoseGraph |
class | PoseGraphEdge |
class | PoseGraphNode |
class | RANSACConvergenceCriteria |
class | RegistrationResult |
Class that contains the registration results. More... | |
class | TransformationEstimation |
class | TransformationEstimationPointToPlane |
Estimate a transformation for point to plane distance. More... | |
class | TransformationEstimationPointToPoint |
Estimate a transformation for point to point distance. More... | |
Typedefs | |
typedef std::vector< Eigen::Vector2i > | CorrespondenceSet |
Functions | |
RegistrationResult | RegistrationColoredICP (const geometry::PointCloud &source, const geometry::PointCloud &target, double max_distance, const Eigen::Matrix4d &init, const ICPConvergenceCriteria &criteria, double lambda_geometric) |
RegistrationResult | FastGlobalRegistration (const geometry::PointCloud &source, const geometry::PointCloud &target, const Feature &source_feature, const Feature &target_feature, const FastGlobalRegistrationOption &option) |
std::shared_ptr< Feature > | ComputeFPFHFeature (const geometry::PointCloud &input, const geometry::KDTreeSearchParam &search_param=geometry::KDTreeSearchParamKNN()) |
Function to compute FPFH feature for a point cloud. More... | |
std::shared_ptr< PoseGraph > | CreatePoseGraphWithoutInvalidEdges (const PoseGraph &pose_graph, const GlobalOptimizationOption &option) |
void | GlobalOptimization (PoseGraph &pose_graph, const GlobalOptimizationMethod &method, const GlobalOptimizationConvergenceCriteria &criteria, const GlobalOptimizationOption &option) |
RegistrationResult | EvaluateRegistration (const geometry::PointCloud &source, const geometry::PointCloud &target, double max_correspondence_distance, const Eigen::Matrix4d &transformation=Eigen::Matrix4d::Identity()) |
Function for evaluation. More... | |
RegistrationResult | RegistrationICP (const geometry::PointCloud &source, const geometry::PointCloud &target, double max_correspondence_distance, const Eigen::Matrix4d &init=Eigen::Matrix4d::Identity(), const TransformationEstimation &estimation=TransformationEstimationPointToPoint(false), const ICPConvergenceCriteria &criteria=ICPConvergenceCriteria()) |
Functions for ICP registration. More... | |
RegistrationResult | RegistrationRANSACBasedOnCorrespondence (const geometry::PointCloud &source, const geometry::PointCloud &target, const CorrespondenceSet &corres, double max_correspondence_distance, const TransformationEstimation &estimation, int ransac_n, const RANSACConvergenceCriteria &criteria) |
RegistrationResult | RegistrationRANSACBasedOnFeatureMatching (const geometry::PointCloud &source, const geometry::PointCloud &target, const Feature &source_feature, const Feature &target_feature, double max_correspondence_distance, const TransformationEstimation &estimation=TransformationEstimationPointToPoint(false), int ransac_n=4, const std::vector< std::reference_wrapper< const CorrespondenceChecker >> &checkers={}, const RANSACConvergenceCriteria &criteria=RANSACConvergenceCriteria()) |
Function for global RANSAC registration based on feature matching. More... | |
Eigen::Matrix6d | GetInformationMatrixFromPointClouds (const geometry::PointCloud &source, const geometry::PointCloud &target, double max_correspondence_distance, const Eigen::Matrix4d &transformation) |
Function for computing information matrix from transformation matrix. More... | |
typedef std::vector<Eigen::Vector2i> open3d::registration::CorrespondenceSet |
std::shared_ptr< Feature > open3d::registration::ComputeFPFHFeature | ( | const geometry::PointCloud & | input, |
const geometry::KDTreeSearchParam & | search_param | ||
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Function to compute FPFH feature for a point cloud.
std::shared_ptr< PoseGraph > open3d::registration::CreatePoseGraphWithoutInvalidEdges | ( | const PoseGraph & | pose_graph, |
const GlobalOptimizationOption & | option | ||
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Function to prune out uncertain edges having confidence_ < .edge_prune_threshold_
RegistrationResult open3d::registration::EvaluateRegistration | ( | const geometry::PointCloud & | source, |
const geometry::PointCloud & | target, | ||
double | max_correspondence_distance, | ||
const Eigen::Matrix4d & | transformation | ||
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Function for evaluation.
RegistrationResult open3d::registration::FastGlobalRegistration | ( | const geometry::PointCloud & | source, |
const geometry::PointCloud & | target, | ||
const Feature & | source_feature, | ||
const Feature & | target_feature, | ||
const FastGlobalRegistrationOption & | option | ||
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Eigen::Matrix6d open3d::registration::GetInformationMatrixFromPointClouds | ( | const geometry::PointCloud & | source, |
const geometry::PointCloud & | target, | ||
double | max_correspondence_distance, | ||
const Eigen::Matrix4d & | transformation | ||
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Function for computing information matrix from transformation matrix.
void open3d::registration::GlobalOptimization | ( | PoseGraph & | pose_graph, |
const GlobalOptimizationMethod & | method = GlobalOptimizationLevenbergMarquardt() , |
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const GlobalOptimizationConvergenceCriteria & | criteria = GlobalOptimizationConvergenceCriteria() , |
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const GlobalOptimizationOption & | option = GlobalOptimizationOption() |
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Function to optimize a PoseGraph Reference: [Kümmerle et al 2011] R Kümmerle, G. Grisetti, H. Strasdat, K. Konolige, W. Burgard g2o: A General Framework for Graph Optimization, ICRA 2011 [Choi et al 2015] S. Choi, Q.-Y. Zhou, V. Koltun, Robust Reconstruction of Indoor Scenes, CVPR 2015 [M. Lourakis 2009] M. Lourakis, SBA: A Software Package for Generic Sparse Bundle Adjustment, Transactions on Mathematical Software, 2009
RegistrationResult open3d::registration::RegistrationColoredICP | ( | const geometry::PointCloud & | source, |
const geometry::PointCloud & | target, | ||
double | max_distance, | ||
const Eigen::Matrix4d & | init = Eigen::Matrix4d::Identity() , |
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const ICPConvergenceCriteria & | criteria = ICPConvergenceCriteria() , |
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double | lambda_geometric = 0.968 |
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Function to align colored point clouds This is implementation of following paper J. Park, Q.-Y. Zhou, V. Koltun, Colored Point Cloud Registration Revisited, ICCV 2017
RegistrationResult open3d::registration::RegistrationICP | ( | const geometry::PointCloud & | source, |
const geometry::PointCloud & | target, | ||
double | max_correspondence_distance, | ||
const Eigen::Matrix4d & | init, | ||
const TransformationEstimation & | estimation, | ||
const ICPConvergenceCriteria & | criteria | ||
) |
Functions for ICP registration.
RegistrationResult open3d::registration::RegistrationRANSACBasedOnCorrespondence | ( | const geometry::PointCloud & | source, |
const geometry::PointCloud & | target, | ||
const CorrespondenceSet & | corres, | ||
double | max_correspondence_distance, | ||
const TransformationEstimation & | estimation = TransformationEstimationPointToPoint(false) , |
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int | ransac_n = 6 , |
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const RANSACConvergenceCriteria & | criteria = RANSACConvergenceCriteria() |
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Function for global RANSAC registration based on a given set of correspondences
RegistrationResult open3d::registration::RegistrationRANSACBasedOnFeatureMatching | ( | const geometry::PointCloud & | source, |
const geometry::PointCloud & | target, | ||
const Feature & | source_feature, | ||
const Feature & | target_feature, | ||
double | max_correspondence_distance, | ||
const TransformationEstimation & | estimation, | ||
int | ransac_n, | ||
const std::vector< std::reference_wrapper< const CorrespondenceChecker >> & | checkers, | ||
const RANSACConvergenceCriteria & | criteria | ||
) |
Function for global RANSAC registration based on feature matching.