Point Cloud Library (PCL)
1.11.1-dev
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43 #include <pcl/registration/correspondence_rejection.h>
47 namespace registration {
53 template <
typename Po
intT>
64 using Ptr = shared_ptr<CorrespondenceRejectorSampleConsensus<PointT>>;
65 using ConstPtr = shared_ptr<const CorrespondenceRejectorSampleConsensus<PointT>>;
104 inline PointCloudConstPtr
const
120 inline PointCloudConstPtr
const
199 inline Eigen::Matrix4f
279 #include <pcl/registration/impl/correspondence_rejection_sample_consensus.hpp>
shared_ptr< CorrespondenceRejector > Ptr
void setTargetPoints(pcl::PCLPointCloud2::ConstPtr cloud2) override
Method for setting the target cloud.
void setSourcePoints(pcl::PCLPointCloud2::ConstPtr cloud2) override
Blob method for setting the source cloud.
shared_ptr< const CorrespondenceRejector > ConstPtr
double getInlierThreshold()
Get the maximum distance between corresponding points.
const std::string & getClassName() const
Get a string representation of the name of this class.
PointCloudConstPtr target_
PointCloud represents the base class in PCL for storing collections of 3D points.
PointCloudPtr input_transformed_
int getMaximumIterations()
Get the maximum number of iterations.
virtual void setInputTarget(const PointCloudConstPtr &cloud)
Provide a target point cloud dataset (must contain XYZ data!)
void getInliersIndices(std::vector< int > &inlier_indices)
Get the inlier indices found by the correspondence rejector.
bool requiresTargetPoints() const override
See if this rejector requires a target cloud.
Eigen::Matrix4f getBestTransformation()
Get the best transformation after RANSAC rejection.
void setMaximumIterations(int max_iterations)
Set the maximum number of iterations.
CorrespondenceRejectorSampleConsensus()
Empty constructor.
shared_ptr< const ::pcl::PCLPointCloud2 > ConstPtr
bool getRefineModel() const
Get the internal refine parameter value as set by the user using setRefineModel.
void setInlierThreshold(double threshold)
Set the maximum distance between corresponding points.
const PointCloudConstPtr getInputSource()
Get a pointer to the input point cloud dataset target.
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
void applyRejection(pcl::Correspondences &correspondences) override
Apply the rejection algorithm.
bool requiresSourcePoints() const override
See if this rejector requires source points.
CorrespondenceRejectorSampleConsensus implements a correspondence rejection using Random Sample Conse...
bool getSaveInliers()
Get whether the rejector is configured to save inliers.
Eigen::Matrix4f best_transformation_
~CorrespondenceRejectorSampleConsensus()
Empty destructor.
shared_ptr< PointCloud< PointT > > Ptr
void setSaveInliers(bool s)
Set whether to save inliers or not.
std::vector< int > inlier_indices_
shared_ptr< const PointCloud< PointT > > ConstPtr
void getRemainingCorrespondences(const pcl::Correspondences &original_correspondences, pcl::Correspondences &remaining_correspondences) override
Get a list of valid correspondences after rejection from the original set of correspondences.
PointCloudConstPtr input_
const PointCloudConstPtr getInputTarget()
Get a pointer to the input point cloud dataset target.
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
void setRefineModel(const bool refine)
Specify whether the model should be refined internally using the variance of the inliers.
virtual void setInputSource(const PointCloudConstPtr &cloud)
Provide a source point cloud dataset (must contain XYZ data!)
CorrespondencesConstPtr input_correspondences_
The input correspondences.
std::string rejection_name_
The name of the rejection method.
Defines functions, macros and traits for allocating and using memory.
CorrespondenceRejector represents the base class for correspondence rejection methods
void fromPCLPointCloud2(const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map)
Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.