43#include <pcl/sample_consensus/sac.h>
44#include <pcl/sample_consensus/sac_model.h>
55 template <
typename Po
intT>
78 , fraction_nr_pretest_ (10.0)
90 , fraction_nr_pretest_ (10.0)
114 double fraction_nr_pretest_;
118#ifdef PCL_NO_PRECOMPILE
119#include <pcl/sample_consensus/impl/rmsac.hpp>
Iterator class for point clouds with or without given indices.
RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized M-estimator...
RandomizedMEstimatorSampleConsensus(const SampleConsensusModelPtr &model, double threshold)
RMSAC (Randomized M-estimator SAmple Consensus) main constructor.
bool computeModel(int debug_verbosity_level=0) override
Compute the actual model and find the inliers.
RandomizedMEstimatorSampleConsensus(const SampleConsensusModelPtr &model)
RMSAC (Randomized M-estimator SAmple Consensus) main constructor.
double getFractionNrPretest() const
Get the percentage of points to pre-test.
void setFractionNrPretest(double nr_pretest)
Set the percentage of points to pre-test.
SampleConsensus represents the base class.
double probability_
Desired probability of choosing at least one sample free from outliers.
Indices inliers_
The indices of the points that were chosen as inliers after the last computeModel () call.
int iterations_
Total number of internal loop iterations that we've done so far.
Indices model_
The model found after the last computeModel () as point cloud indices.
Eigen::VectorXf model_coefficients_
The coefficients of our model computed directly from the model found.
double threshold_
Distance to model threshold.
SampleConsensusModelPtr sac_model_
The underlying data model used (i.e.
int max_iterations_
Maximum number of iterations before giving up.
shared_ptr< SampleConsensusModel< PointT > > Ptr
A point structure representing Euclidean xyz coordinates, and the RGB color.