43#include <pcl/sample_consensus/sac.h>
44#include <pcl/sample_consensus/sac_model.h>
45#include <pcl/pcl_base.h>
56 template <
typename Po
intT>
137 getMinMax (
const PointCloudConstPtr &cloud,
139 Eigen::Vector4f &
min_p,
140 Eigen::Vector4f &
max_p)
const;
150 Eigen::Vector4f &
median)
const;
160#ifdef PCL_NO_PRECOMPILE
161#include <pcl/sample_consensus/impl/mlesac.hpp>
Iterator class for point clouds with or without given indices.
MaximumLikelihoodSampleConsensus represents an implementation of the MLESAC (Maximum Likelihood Estim...
void computeMedian(const PointCloudConstPtr &cloud, const IndicesPtr &indices, Eigen::Vector4f &median) const
Compute the median value of a 3D point cloud using a given set point indices and return it as a Point...
MaximumLikelihoodSampleConsensus(const SampleConsensusModelPtr &model)
MLESAC (Maximum Likelihood Estimator SAmple Consensus) main constructor.
MaximumLikelihoodSampleConsensus(const SampleConsensusModelPtr &model, double threshold)
MLESAC (Maximum Likelihood Estimator SAmple Consensus) main constructor.
int getEMIterations() const
Get the number of EM iterations.
void setEMIterations(int iterations)
Set the number of EM iterations.
void getMinMax(const PointCloudConstPtr &cloud, const IndicesPtr &indices, Eigen::Vector4f &min_p, Eigen::Vector4f &max_p) const
Determine the minimum and maximum 3D bounding box coordinates for a given set of points.
bool computeModel(int debug_verbosity_level=0) override
Compute the actual model and find the inliers.
double computeMedianAbsoluteDeviation(const PointCloudConstPtr &cloud, const IndicesPtr &indices, double sigma) const
Compute the median absolute deviation:
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
typename PointCloud::ConstPtr PointCloudConstPtr
shared_ptr< Indices > IndicesPtr
A point structure representing Euclidean xyz coordinates, and the RGB color.