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SampleConsensusModel1PointPlane defines a model for 3D plane segmentation. More...
#include </__w/1/s/cuda/sample_consensus/include/pcl/cuda/sample_consensus/sac_model_1point_plane.h >
SampleConsensusModel1PointPlane (const PointCloudConstPtr &cloud)
Constructor for base SampleConsensusModel1PointPlane . More...
void
getSamples (int &iterations, Indices &samples)
Get 3 random non-collinear points as data samples and return them as point indices. More...
bool
computeModelCoefficients (const Indices &samples, Coefficients &model_coefficients)
Check whether the given index samples can form a valid plane model, compute the model coefficients from these samples and store them in model_coefficients. More...
bool
generateModelHypotheses (Hypotheses &h, int max_iterations)
bool
generateModelHypotheses (Hypotheses &h, Samples &s, int max_iterations)
int
selectWithinDistance (const Coefficients &model_coefficients, float threshold, IndicesPtr &inliers, IndicesPtr &inliers_stencil)
Select all the points which respect the given model coefficients as inliers. More...
int
selectWithinDistance (const Hypotheses &h, int idx, float threshold, IndicesPtr &inliers, IndicesPtr &inliers_stencil)
int
selectWithinDistance (Hypotheses &h, int idx, float threshold, IndicesPtr &inliers_stencil, float3 ¢roid)
int
countWithinDistance (const Coefficients &model_coefficients, float threshold)
int
countWithinDistance (const Hypotheses &h, int idx, float threshold)
SampleConsensusModel (const PointCloudConstPtr &cloud)
Constructor for base SampleConsensusModel . More...
virtual
~SampleConsensusModel ()=default
Destructor for base SampleConsensusModel . More...
virtual bool
isSampleInlier (IndicesPtr &inliers_stencil, Samples &samples, unsigned int &i)
int
deleteIndices (const IndicesPtr &indices_stencil)
int
deleteIndices (const Hypotheses &h, int idx, IndicesPtr &inliers, const IndicesPtr &inliers_delete)
virtual void
setInputCloud (const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset. More...
PointCloudConstPtr
getInputCloud () const
Get a pointer to the input point cloud dataset. More...
IndicesPtr
getIndices () const
Get a pointer to the vector of indices used. More...
void
setRadiusLimits (float min_radius, float max_radius)
Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate a radius) More...
void
getRadiusLimits (float &min_radius, float &max_radius)
Get the minimum and maximum allowable radius limits for the model as set by the user. More...
shared_ptr< typename Storage< float4 >::type >
getNormals ()
void
setNormals (shared_ptr< typename Storage< float4 >::type > normals)
template<template< typename > class Storage> class pcl::cuda::SampleConsensusModel1PointPlane< Storage > SampleConsensusModel1PointPlane defines a model for 3D plane segmentation.
Definition at line 157 of file sac_model_1point_plane.h .
Coefficients template<template< typename > class Storage>
ConstPtr template<template< typename > class Storage>
Hypotheses template<template< typename > class Storage>
Indices template<template< typename > class Storage>
IndicesConstPtr template<template< typename > class Storage>
IndicesPtr template<template< typename > class Storage>
PointCloud template<template< typename > class Storage>
PointCloudConstPtr template<template< typename > class Storage>
PointCloudPtr template<template< typename > class Storage>
Ptr template<template< typename > class Storage>
Samples template<template< typename > class Storage>
SampleConsensusModel1PointPlane() template<template< typename > class Storage>
computeModelCoefficients() template<template< typename > class Storage>
Check whether the given index samples can form a valid plane model, compute the model coefficients from these samples and store them in model_coefficients.
The plane coefficients are: a, b, c, d (ax+by+cz+d=0)
Parameters
samples
the point indices found as possible good candidates for creating a valid model
model_coefficients
the resultant model coefficients
Implements pcl::cuda::SampleConsensusModel< Storage > .
countWithinDistance() [1/2]
template<template< typename > class Storage>
countWithinDistance() [2/2]
template<template< typename > class Storage>
generateModelHypotheses() [1/2]
template<template< typename > class Storage>
generateModelHypotheses() [2/2]
template<template< typename > class Storage>
getSamples() template<template< typename > class Storage>
Get 3 random non-collinear points as data samples and return them as point indices.
Parameters
iterations
the internal number of iterations used by SAC methods
samples
the resultant model samples
Note
assumes unique points!
Implements pcl::cuda::SampleConsensusModel< Storage > .
selectWithinDistance() [1/3]
template<template< typename > class Storage>
Select all the points which respect the given model coefficients as inliers.
Parameters
model_coefficients
the coefficients of a plane model that we need to compute distances to
threshold
a maximum admissible distance threshold for determining the inliers from the outliers
inliers
the resultant model inliers
inliers_stencil
Implements pcl::cuda::SampleConsensusModel< Storage > .
selectWithinDistance() [2/3]
template<template< typename > class Storage>
selectWithinDistance() [3/3]
template<template< typename > class Storage>
MAX_ITERATIONS_COLLINEAR template<template< typename > class Storage>
The documentation for this class was generated from the following file: