pcl::ndt2d::NormalDist< PointT > Class Template Reference

A normal distribution estimation class. More...

#include <pcl/registration/impl/ndt_2d.hpp>

Public Member Functions
	NormalDist ()=default
void	addIdx (std::size_t i)
	Store a point index to use later for estimating distribution parameters. More...
void	estimateParams (const PointCloud &cloud, double min_covar_eigvalue_mult=0.001)
	Estimate the normal distribution parameters given the point indices provided. More...
ValueAndDerivatives< 3, double >	test (const PointT &transformed_pt, const double &cos_theta, const double &sin_theta) const
	Return the 'score' (denormalised likelihood) and derivatives of score of the point p given this distribution. More...

Protected Attributes
const std::size_t	min_n_ {3}
std::size_t	n_ {0}
std::vector< std::size_t >	pt_indices_
Eigen::Vector2d	mean_
Eigen::Matrix2d	covar_inv_

Detailed Description

template<typename PointT>
class pcl::ndt2d::NormalDist< PointT >

A normal distribution estimation class.

First the indices of of the points from a point cloud that should be modelled by the distribution are added with addIdx (...).

Then estimateParams (...) uses the stored point indices to estimate the parameters of a normal distribution, and discards the stored indices.

Finally the distriubution, and its derivatives, may be evaluated at any point using test (...).

Definition at line 98 of file ndt_2d.hpp.

Constructor & Destructor Documentation

NormalDist()

template<typename PointT >

pcl::ndt2d::NormalDist< PointT >::NormalDist ( )

default

Member Function Documentation

addIdx()

template<typename PointT >

void pcl::ndt2d::NormalDist< PointT >::addIdx ( std::size_t  i )

inline

Store a point index to use later for estimating distribution parameters.

Parameters

[in]

i

Point index to store

Definition at line 108 of file ndt_2d.hpp.

References pcl::ndt2d::NormalDist< PointT >::pt_indices_.

estimateParams()

template<typename PointT >

void pcl::ndt2d::NormalDist< PointT >::estimateParams ( const PointCloud &  cloud, double  min_covar_eigvalue_mult = 0.001  )

inline

Estimate the normal distribution parameters given the point indices provided.

Memory of point indices is cleared.

Parameters

[in]	cloud	Point cloud corresponding to indices passed to addIdx.
[in]	min_covar_eigvalue_mult	Set the smallest eigenvalue to this times the largest.

Definition at line 119 of file ndt_2d.hpp.

References pcl::ndt2d::NormalDist< PointT >::covar_inv_, pcl::ndt2d::NormalDist< PointT >::mean_, pcl::ndt2d::NormalDist< PointT >::min_n_, pcl::ndt2d::NormalDist< PointT >::n_, and pcl::ndt2d::NormalDist< PointT >::pt_indices_.

test()

template<typename PointT >

ValueAndDerivatives<3, double> pcl::ndt2d::NormalDist< PointT >::test ( const PointT &  transformed_pt, const double &  cos_theta, const double &  sin_theta  ) const

inline

Return the 'score' (denormalised likelihood) and derivatives of score of the point p given this distribution.

Parameters

[in]	transformed_pt	Location to evaluate at.
[in]	cos_theta	sin(theta) of the current rotation angle of rigid transformation: to avoid repeated evaluation
[in]	sin_theta	cos(theta) of the current rotation angle of rigid transformation: to avoid repeated evaluation estimateParams must have been called after at least three points were provided, or this will return zero.

Definition at line 166 of file ndt_2d.hpp.

References pcl::ndt2d::NormalDist< PointT >::covar_inv_, pcl::ndt2d::ValueAndDerivatives< N, T >::grad, pcl::ndt2d::ValueAndDerivatives< N, T >::hessian, pcl::ndt2d::NormalDist< PointT >::mean_, pcl::ndt2d::NormalDist< PointT >::min_n_, pcl::ndt2d::NormalDist< PointT >::n_, pcl::ndt2d::ValueAndDerivatives< N, T >::value, and pcl::ndt2d::ValueAndDerivatives< N, T >::Zero().

Referenced by pcl::ndt2d::NDTSingleGrid< PointT >::test().

Member Data Documentation

covar_inv_

template<typename PointT >

Eigen::Matrix2d pcl::ndt2d::NormalDist< PointT >::covar_inv_

protected

Definition at line 211 of file ndt_2d.hpp.

Referenced by pcl::ndt2d::NormalDist< PointT >::estimateParams(), and pcl::ndt2d::NormalDist< PointT >::test().

mean_

template<typename PointT >

Eigen::Vector2d pcl::ndt2d::NormalDist< PointT >::mean_

protected

Definition at line 210 of file ndt_2d.hpp.

Referenced by pcl::ndt2d::NormalDist< PointT >::estimateParams(), and pcl::ndt2d::NormalDist< PointT >::test().

min_n_

template<typename PointT >

const std::size_t pcl::ndt2d::NormalDist< PointT >::min_n_ {3}

protected

Definition at line 206 of file ndt_2d.hpp.

Referenced by pcl::ndt2d::NormalDist< PointT >::estimateParams(), and pcl::ndt2d::NormalDist< PointT >::test().

n_

template<typename PointT >

std::size_t pcl::ndt2d::NormalDist< PointT >::n_ {0}

protected

Definition at line 208 of file ndt_2d.hpp.

Referenced by pcl::ndt2d::NormalDist< PointT >::estimateParams(), and pcl::ndt2d::NormalDist< PointT >::test().

pt_indices_

template<typename PointT >

std::vector<std::size_t> pcl::ndt2d::NormalDist< PointT >::pt_indices_

protected

Definition at line 209 of file ndt_2d.hpp.

Referenced by pcl::ndt2d::NormalDist< PointT >::addIdx(), and pcl::ndt2d::NormalDist< PointT >::estimateParams().

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The documentation for this class was generated from the following file:

• pcl/registration/impl/ndt_2d.hpp