Private Member Functions
pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, Eigen::MatrixXf > Class Template Reference

PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals. More...

#include <principal_curvatures.h>

Inheritance diagram for pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, Eigen::MatrixXf >:
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Private Member Functions

void compute (pcl::PointCloud< pcl::Normal > &)
 Make the compute (&PointCloudOut); inaccessible from outside the class.
void computeFeatureEigen (pcl::PointCloud< Eigen::MatrixXf > &output)
 Estimate the principal curvature (eigenvector of the max eigenvalue), along with both the max (pc1) and min (pc2) eigenvalues for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()

Detailed Description

template<typename PointInT, typename PointNT>
class pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, Eigen::MatrixXf >

PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals.

Note:
The code is stateful as we do not expect this class to be multicore parallelized. Please look at NormalEstimationOMP for an example on how to extend this to parallel implementations.
Author:
Radu B. Rusu, Jared Glover

Definition at line 150 of file principal_curvatures.h.


Member Function Documentation

template<typename PointInT , typename PointNT >
void pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, Eigen::MatrixXf >::compute ( pcl::PointCloud< pcl::Normal > &  ) [inline, private]

Make the compute (&PointCloudOut); inaccessible from outside the class.

Parameters:
[out]outputthe output point cloud

Definition at line 174 of file principal_curvatures.h.

template<typename PointInT , typename PointNT >
void pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, Eigen::MatrixXf >::computeFeatureEigen ( pcl::PointCloud< Eigen::MatrixXf > &  output) [private, virtual]

Estimate the principal curvature (eigenvector of the max eigenvalue), along with both the max (pc1) and min (pc2) eigenvalues for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()

Parameters:
[out]outputthe resultant point cloud model dataset that contains the principal curvature estimates

Reimplemented from pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, pcl::PrincipalCurvatures >.

Definition at line 164 of file principal_curvatures.hpp.


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


pcl
Author(s): Open Perception
autogenerated on Mon Oct 6 2014 03:19:52