Classes | Functions

Module sample_consensus


Detailed Description

Overview

The pcl_sample_consensus library holds SAmple Consensus (SAC) methods like RANSAC and models like planes and cylinders. These can combined freely in order to detect specific models and their paramters in point clouds.

Some of the models implemented in this library include: lines, planes, cylinders, and spheres. Plane fitting is often applied to the task of detecting common indoor surfaces, such as walls, floors, and table tops. Other models can be used to detect and segment objects with common geometric structures (e.g., fitting a cylinder model to a mug).

sample_consensus_planes_cylinders.png

As of PCL 1.0, the following models are supported:

The following list describes the robust sample consensus estimators implemented:

By default, if you're not familiar with most of the above estimators and how they operate, use RANSAC to test your hypotheses.

History

Requirements

Classes

class  pcl::LeastMedianSquares< PointT >
 LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm. More...
class  pcl::MaximumLikelihoodSampleConsensus< PointT >
 MaximumLikelihoodSampleConsensus represents an implementation of the MLESAC (Maximum Likelihood Estimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S. More...
class  pcl::MEstimatorSampleConsensus< PointT >
 MEstimatorSampleConsensus represents an implementation of the MSAC (M-estimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S. More...
class  pcl::ProgressiveSampleConsensus< PointT >
 RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm, as described in: "Matching with PROSAC – Progressive Sample Consensus", Chum, O. More...
class  pcl::RandomSampleConsensus< PointT >
 RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm, as described in: "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography", Martin A. More...
class  pcl::RandomizedMEstimatorSampleConsensus< PointT >
 RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized M-estimator SAmple Consensus) algorithm, which basically adds a Td,d test (see RandomizedRandomSampleConsensus) to an MSAC estimator (see MEstimatorSampleConsensus). More...
class  pcl::RandomizedRandomSampleConsensus< PointT >
 RandomizedRandomSampleConsensus represents an implementation of the RRANSAC (Randomized RAndom SAmple Consensus), as described in "Randomized RANSAC with Td,d test", O. More...
class  pcl::SampleConsensus< T >
 SampleConsensus represents the base class. More...
class  pcl::SampleConsensusModel< PointT >
 SampleConsensusModel represents the base model class. More...
class  pcl::SampleConsensusModelCircle2D< PointT >
 SampleConsensusModelCircle2D defines a model for 2D circle segmentation on the X-Y plane. More...
class  pcl::SampleConsensusModelCylinder< PointT, PointNT >
 SampleConsensusModelCylinder defines a model for 3D cylinder segmentation. More...
class  pcl::SampleConsensusModelLine< PointT >
 SampleConsensusModelLine defines a model for 3D line segmentation. More...
class  pcl::SampleConsensusModelNormalParallelPlane< PointT, PointNT >
 SampleConsensusModelNormalParallelPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...
class  pcl::SampleConsensusModelNormalPlane< PointT, PointNT >
 SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...
class  pcl::SampleConsensusModelParallelLine< PointT >
 SampleConsensusModelParallelLine defines a model for 3D line segmentation using additional angular constraints. More...
class  pcl::SampleConsensusModelParallelPlane< PointT >
 SampleConsensusModelParallelPlane defines a model for 3D plane segmentation using additional angular constraints. More...
class  pcl::SampleConsensusModelPerpendicularPlane< PointT >
 SampleConsensusModelPerpendicularPlane defines a model for 3D plane segmentation using additional angular constraints. More...
class  pcl::SampleConsensusModelPlane< PointT >
 SampleConsensusModelPlane defines a model for 3D plane segmentation. More...
class  pcl::SampleConsensusModelRegistration< PointT >
 SampleConsensusModelRegistration defines a model for Point-To-Point registration outlier rejection. More...
class  pcl::SampleConsensusModelSphere< PointT >
 SampleConsensusModelSphere defines a model for 3D sphere segmentation. More...

Functions

template<typename Point >
double pcl::pointToPlaneDistanceSigned (const Point &p, double a, double b, double c, double d)
 Get the distance from a point to a plane (signed) defined by ax+by+cz+d=0.
template<typename Point >
double pcl::pointToPlaneDistanceSigned (const Point &p, const Eigen::Vector4f &plane_coefficients)
 Get the distance from a point to a plane (signed) defined by ax+by+cz+d=0.
template<typename Point >
double pcl::pointToPlaneDistance (const Point &p, double a, double b, double c, double d)
 Get the distance from a point to a plane (unsigned) defined by ax+by+cz+d=0.
template<typename Point >
double pcl::pointToPlaneDistance (const Point &p, const Eigen::Vector4f &plane_coefficients)
 Get the distance from a point to a plane (unsigned) defined by ax+by+cz+d=0.

Function Documentation

template<typename Point >
double pcl::pointToPlaneDistance ( const Point &  p,
double  a,
double  b,
double  c,
double  d 
) [inline]

Get the distance from a point to a plane (unsigned) defined by ax+by+cz+d=0.

Parameters:
p a point
a the normalized a coefficient of a plane
b the normalized b coefficient of a plane
c the normalized c coefficient of a plane
d the normalized d coefficient of a plane

Definition at line 80 of file sac_model_plane.h.

template<typename Point >
double pcl::pointToPlaneDistance ( const Point &  p,
const Eigen::Vector4f &  plane_coefficients 
) [inline]

Get the distance from a point to a plane (unsigned) defined by ax+by+cz+d=0.

Parameters:
p a point
plane_coefficients the normalized coefficients (a, b, c, d) of a plane

Definition at line 91 of file sac_model_plane.h.

template<typename Point >
double pcl::pointToPlaneDistanceSigned ( const Point &  p,
double  a,
double  b,
double  c,
double  d 
) [inline]

Get the distance from a point to a plane (signed) defined by ax+by+cz+d=0.

Parameters:
p a point
a the normalized a coefficient of a plane
b the normalized b coefficient of a plane
c the normalized c coefficient of a plane
d the normalized d coefficient of a plane

Definition at line 55 of file sac_model_plane.h.

template<typename Point >
double pcl::pointToPlaneDistanceSigned ( const Point &  p,
const Eigen::Vector4f &  plane_coefficients 
) [inline]

Get the distance from a point to a plane (signed) defined by ax+by+cz+d=0.

Parameters:
p a point
plane_coefficients the normalized coefficients (a, b, c, d) of a plane

Definition at line 66 of file sac_model_plane.h.