Point Cloud Library (PCL)
1.10.0
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MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation. More...
#include <pcl/surface/mls.h>
Classes | |
class | MLSVoxelGrid |
A minimalistic implementation of a voxel grid, necessary for the point cloud upsampling. More... | |
Public Member Functions | |
MovingLeastSquares () | |
Empty constructor. More... | |
~MovingLeastSquares () | |
Empty destructor. More... | |
void | setComputeNormals (bool compute_normals) |
Set whether the algorithm should also store the normals computed. More... | |
void | setSearchMethod (const KdTreePtr &tree) |
Provide a pointer to the search object. More... | |
KdTreePtr | getSearchMethod () const |
Get a pointer to the search method used. More... | |
void | setPolynomialOrder (int order) |
Set the order of the polynomial to be fit. More... | |
int | getPolynomialOrder () const |
Get the order of the polynomial to be fit. More... | |
void | setPolynomialFit (bool polynomial_fit) |
Sets whether the surface and normal are approximated using a polynomial, or only via tangent estimation. More... | |
bool | getPolynomialFit () const |
Get the polynomial_fit value (true if the surface and normal are approximated using a polynomial). More... | |
void | setSearchRadius (double radius) |
Set the sphere radius that is to be used for determining the k-nearest neighbors used for fitting. More... | |
double | getSearchRadius () const |
Get the sphere radius used for determining the k-nearest neighbors. More... | |
void | setSqrGaussParam (double sqr_gauss_param) |
Set the parameter used for distance based weighting of neighbors (the square of the search radius works best in general). More... | |
double | getSqrGaussParam () const |
Get the parameter for distance based weighting of neighbors. More... | |
void | setUpsamplingMethod (UpsamplingMethod method) |
Set the upsampling method to be used. More... | |
void | setDistinctCloud (PointCloudInConstPtr distinct_cloud) |
Set the distinct cloud used for the DISTINCT_CLOUD upsampling method. More... | |
PointCloudInConstPtr | getDistinctCloud () const |
Get the distinct cloud used for the DISTINCT_CLOUD upsampling method. More... | |
void | setUpsamplingRadius (double radius) |
Set the radius of the circle in the local point plane that will be sampled. More... | |
double | getUpsamplingRadius () const |
Get the radius of the circle in the local point plane that will be sampled. More... | |
void | setUpsamplingStepSize (double step_size) |
Set the step size for the local plane sampling. More... | |
double | getUpsamplingStepSize () const |
Get the step size for the local plane sampling. More... | |
void | setPointDensity (int desired_num_points_in_radius) |
Set the parameter that specifies the desired number of points within the search radius. More... | |
int | getPointDensity () const |
Get the parameter that specifies the desired number of points within the search radius. More... | |
void | setDilationVoxelSize (float voxel_size) |
Set the voxel size for the voxel grid. More... | |
float | getDilationVoxelSize () const |
Get the voxel size for the voxel grid. More... | |
void | setDilationIterations (int iterations) |
Set the number of dilation steps of the voxel grid. More... | |
int | getDilationIterations () const |
Get the number of dilation steps of the voxel grid. More... | |
void | setCacheMLSResults (bool cache_mls_results) |
Set whether the mls results should be stored for each point in the input cloud. More... | |
bool | getCacheMLSResults () const |
Get the cache_mls_results_ value (True if the mls results should be stored, otherwise false). More... | |
void | setProjectionMethod (MLSResult::ProjectionMethod method) |
Set the method to be used when projection the point on to the MLS surface. More... | |
MLSResult::ProjectionMethod | getProjectionMethod () const |
Get the current projection method being used. More... | |
const std::vector< MLSResult > & | getMLSResults () const |
Get the MLSResults for input cloud. More... | |
void | setNumberOfThreads (unsigned int threads=1) |
Set the maximum number of threads to use. More... | |
void | process (PointCloudOut &output) override |
Base method for surface reconstruction for all points given in <setInputCloud (), setIndices ()> More... | |
PointIndicesPtr | getCorrespondingIndices () const |
Get the set of indices with each point in output having the corresponding point in input. More... | |
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CloudSurfaceProcessing () | |
Constructor. More... | |
~CloudSurfaceProcessing () | |
Empty destructor. More... | |
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PCLBase () | |
Empty constructor. More... | |
PCLBase (const PCLBase &base) | |
Copy constructor. More... | |
virtual | ~PCLBase () |
Destructor. More... | |
virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
Provide a pointer to the input dataset. More... | |
const PointCloudConstPtr | getInputCloud () const |
Get a pointer to the input point cloud dataset. More... | |
virtual void | setIndices (const IndicesPtr &indices) |
Provide a pointer to the vector of indices that represents the input data. More... | |
virtual void | setIndices (const IndicesConstPtr &indices) |
Provide a pointer to the vector of indices that represents the input data. More... | |
virtual void | setIndices (const PointIndicesConstPtr &indices) |
Provide a pointer to the vector of indices that represents the input data. More... | |
virtual void | setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols) |
Set the indices for the points laying within an interest region of the point cloud. More... | |
const IndicesPtr | getIndices () |
Get a pointer to the vector of indices used. More... | |
const IndicesConstPtr | getIndices () const |
Get a pointer to the vector of indices used. More... | |
const PointInT & | operator[] (std::size_t pos) const |
Override PointCloud operator[] to shorten code. More... | |
Protected Member Functions | |
int | searchForNeighbors (int index, std::vector< int > &indices, std::vector< float > &sqr_distances) const |
Search for the closest nearest neighbors of a given point using a radius search. More... | |
void | computeMLSPointNormal (int index, const std::vector< int > &nn_indices, PointCloudOut &projected_points, NormalCloud &projected_points_normals, PointIndices &corresponding_input_indices, MLSResult &mls_result) const |
Smooth a given point and its neighborghood using Moving Least Squares. More... | |
void | addProjectedPointNormal (int index, const Eigen::Vector3d &point, const Eigen::Vector3d &normal, double curvature, PointCloudOut &projected_points, NormalCloud &projected_points_normals, PointIndices &corresponding_input_indices) const |
This is a helper function for add projected points. More... | |
void | copyMissingFields (const PointInT &point_in, PointOutT &point_out) const |
void | performProcessing (PointCloudOut &output) override |
Abstract surface reconstruction method. More... | |
void | performUpsampling (PointCloudOut &output) |
Perform upsampling for the distinct-cloud and voxel-grid methods. More... | |
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bool | initCompute () |
This method should get called before starting the actual computation. More... | |
bool | deinitCompute () |
This method should get called after finishing the actual computation. More... | |
Protected Attributes | |
NormalCloudPtr | normals_ |
The point cloud that will hold the estimated normals, if set. More... | |
PointCloudInConstPtr | distinct_cloud_ |
The distinct point cloud that will be projected to the MLS surface. More... | |
SearchMethod | search_method_ |
The search method template for indices. More... | |
KdTreePtr | tree_ |
A pointer to the spatial search object. More... | |
int | order_ |
The order of the polynomial to be fit. More... | |
double | search_radius_ |
The nearest neighbors search radius for each point. More... | |
double | sqr_gauss_param_ |
Parameter for distance based weighting of neighbors (search_radius_ * search_radius_ works fine) More... | |
bool | compute_normals_ |
Parameter that specifies whether the normals should be computed for the input cloud or not. More... | |
UpsamplingMethod | upsample_method_ |
Parameter that specifies the upsampling method to be used. More... | |
double | upsampling_radius_ |
Radius of the circle in the local point plane that will be sampled. More... | |
double | upsampling_step_ |
Step size for the local plane sampling. More... | |
int | desired_num_points_in_radius_ |
Parameter that specifies the desired number of points within the search radius. More... | |
bool | cache_mls_results_ |
True if the mls results for the input cloud should be stored. More... | |
std::vector< MLSResult > | mls_results_ |
Stores the MLS result for each point in the input cloud. More... | |
MLSResult::ProjectionMethod | projection_method_ |
Parameter that specifies the projection method to be used. More... | |
unsigned int | threads_ |
The maximum number of threads the scheduler should use. More... | |
float | voxel_size_ |
Voxel size for the VOXEL_GRID_DILATION upsampling method. More... | |
int | dilation_iteration_num_ |
Number of dilation steps for the VOXEL_GRID_DILATION upsampling method. More... | |
int | nr_coeff_ |
Number of coefficients, to be computed from the requested order. More... | |
PointIndicesPtr | corresponding_input_indices_ |
Collects for each point in output the corrseponding point in the input. More... | |
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PointCloudConstPtr | input_ |
The input point cloud dataset. More... | |
IndicesPtr | indices_ |
A pointer to the vector of point indices to use. More... | |
bool | use_indices_ |
Set to true if point indices are used. More... | |
bool | fake_indices_ |
If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More... | |
MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation.
It also contains methods for upsampling the resulting cloud based on the parametric fit. Reference paper: "Computing and Rendering Point Set Surfaces" by Marc Alexa, Johannes Behr, Daniel Cohen-Or, Shachar Fleishman, David Levin and Claudio T. Silva www.sci.utah.edu/~shachar/Publications/crpss.pdf
typedef shared_ptr<const MovingLeastSquares<PointInT, PointOutT> > pcl::MovingLeastSquares< PointInT, PointOutT >::ConstPtr |
using pcl::MovingLeastSquares< PointInT, PointOutT >::KdTree = pcl::search::Search<PointInT> |
using pcl::MovingLeastSquares< PointInT, PointOutT >::KdTreePtr = typename KdTree::Ptr |
using pcl::MovingLeastSquares< PointInT, PointOutT >::NormalCloud = pcl::PointCloud<pcl::Normal> |
using pcl::MovingLeastSquares< PointInT, PointOutT >::NormalCloudPtr = NormalCloud::Ptr |
using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudIn = pcl::PointCloud<PointInT> |
using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudInConstPtr = typename PointCloudIn::ConstPtr |
using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudInPtr = typename PointCloudIn::Ptr |
using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudOut = pcl::PointCloud<PointOutT> |
using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudOutConstPtr = typename PointCloudOut::ConstPtr |
using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudOutPtr = typename PointCloudOut::Ptr |
typedef shared_ptr<MovingLeastSquares<PointInT, PointOutT> > pcl::MovingLeastSquares< PointInT, PointOutT >::Ptr |
using pcl::MovingLeastSquares< PointInT, PointOutT >::SearchMethod = std::function<int (int, double, std::vector<int> &, std::vector<float> &)> |
enum pcl::MovingLeastSquares::UpsamplingMethod |
Enumerator | |
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NONE | No upsampling will be done, only the input points will be projected to their own MLS surfaces. |
DISTINCT_CLOUD | Project the points of the distinct cloud to the MLS surface. |
SAMPLE_LOCAL_PLANE | The local plane of each input point will be sampled in a circular fashion using the upsampling_radius_ and the upsampling_step_ parameters. |
RANDOM_UNIFORM_DENSITY | The local plane of each input point will be sampled using an uniform random distribution such that the density of points is constant throughout the cloud - given by the desired_num_points_in_radius_ parameter. |
VOXEL_GRID_DILATION | The input cloud will be inserted into a voxel grid with voxels of size voxel_size_; this voxel grid will be dilated dilation_iteration_num_ times and the resulting points will be projected to the MLS surface of the closest point in the input cloud; the result is a point cloud with filled holes and a constant point density. |
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This is a helper function for add projected points.
[in] | index | the index of the query point in the input cloud |
[in] | point | the projected point to be added |
[in] | normal | the projected point's normal to be added |
[in] | curvature | the projected point's curvature |
[out] | projected_points | the set of projected points around the query point |
[out] | projected_points_normals | the normals corresponding to the projected points |
[out] | corresponding_input_indices | the set of indices with each point in output having the corresponding point in input |
Definition at line 248 of file mls.hpp.
References pcl::_Normal::curvature, pcl::PointIndices::indices, and pcl::PointCloud< PointT >::push_back().
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Smooth a given point and its neighborghood using Moving Least Squares.
[in] | index | the index of the query point in the input cloud |
[in] | nn_indices | the set of nearest neighbors indices for pt |
[out] | projected_points | the set of points projected points around the query point (in the case of upsampling method NONE, only the query point projected to its own fitted surface will be returned, in the case of the other upsampling methods, multiple points will be returned) |
[out] | projected_points_normals | the normals corresponding to the projected points |
[out] | corresponding_input_indices | the set of indices with each point in output having the corresponding point in input |
[out] | mls_result | stores the MLS result for each point in the input cloud (used only in the case of VOXEL_GRID_DILATION or DISTINCT_CLOUD upsampling) |
Definition at line 170 of file mls.hpp.
References pcl::MLSResult::computeMLSSurface(), pcl::MLSResult::curvature, pcl::MLSResult::MLSProjectionResults::normal, pcl::MLSResult::num_neighbors, pcl::MLSResult::MLSProjectionResults::point, pcl::MLSResult::projectPointSimpleToPolynomialSurface(), pcl::MLSResult::projectPointToMLSPlane(), and pcl::MLSResult::projectQueryPoint().
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Definition at line 887 of file mls.hpp.
References pcl::copyPoint().
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Get the cache_mls_results_ value (True if the mls results should be stored, otherwise false).
Definition at line 497 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::cache_mls_results_.
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Get the set of indices with each point in output having the corresponding point in input.
Definition at line 537 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::corresponding_input_indices_.
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Get the number of dilation steps of the voxel grid.
Definition at line 485 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::dilation_iteration_num_.
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Get the voxel size for the voxel grid.
Definition at line 472 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::voxel_size_.
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Get the distinct cloud used for the DISTINCT_CLOUD upsampling method.
Definition at line 415 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::distinct_cloud_.
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Get the MLSResults for input cloud.
Definition at line 516 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::mls_results_.
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Get the parameter that specifies the desired number of points within the search radius.
Definition at line 458 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::desired_num_points_in_radius_.
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Get the polynomial_fit value (true if the surface and normal are approximated using a polynomial).
Definition at line 379 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::order_.
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Get the order of the polynomial to be fit.
Definition at line 354 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::order_.
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Get the current projection method being used.
Definition at line 509 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::projection_method_.
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Get a pointer to the search method used.
Definition at line 343 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::tree_.
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Get the sphere radius used for determining the k-nearest neighbors.
Definition at line 390 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::search_radius_.
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Get the parameter for distance based weighting of neighbors.
Definition at line 401 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::sqr_gauss_param_.
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Get the radius of the circle in the local point plane that will be sampled.
Definition at line 429 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::upsampling_radius_.
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Get the step size for the local plane sampling.
Definition at line 443 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::upsampling_step_.
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Abstract surface reconstruction method.
[out] | output | the result of the reconstruction |
Implements pcl::CloudSurfaceProcessing< PointInT, PointOutT >.
Definition at line 280 of file mls.hpp.
References pcl::PointCloud< PointT >::begin(), pcl::PointCloud< PointT >::end(), pcl::PointCloud< PointT >::insert(), and pcl::PointCloud< PointT >::size().
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Perform upsampling for the distinct-cloud and voxel-grid methods.
[out] | output | the result of the reconstruction |
Definition at line 364 of file mls.hpp.
References pcl::MovingLeastSquares< PointInT, PointOutT >::MLSVoxelGrid::dilate(), pcl::MovingLeastSquares< PointInT, PointOutT >::MLSVoxelGrid::getPosition(), pcl::MLSResult::MLSProjectionResults::normal, pcl::MLSResult::MLSProjectionResults::point, and pcl::MovingLeastSquares< PointInT, PointOutT >::MLSVoxelGrid::voxel_grid_.
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Base method for surface reconstruction for all points given in <setInputCloud (), setIndices ()>
[out] | output | the resultant reconstructed surface model |
Reimplemented from pcl::CloudSurfaceProcessing< PointInT, PointOutT >.
Definition at line 57 of file mls.hpp.
References pcl::PointCloud< PointT >::header, pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::points, pcl::PointCloud< PointT >::size(), and pcl::PointCloud< PointT >::width.
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Search for the closest nearest neighbors of a given point using a radius search.
[in] | index | the index of the query point |
[out] | indices | the resultant vector of indices representing the k-nearest neighbors |
[out] | sqr_distances | the resultant squared distances from the query point to the k-nearest neighbors |
Definition at line 674 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::search_method_, and pcl::MovingLeastSquares< PointInT, PointOutT >::search_radius_.
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Set whether the mls results should be stored for each point in the input cloud.
[in] | True | if the mls results should be stored, otherwise false. |
Definition at line 493 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::cache_mls_results_.
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Set whether the algorithm should also store the normals computed.
Definition at line 325 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::compute_normals_.
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Set the number of dilation steps of the voxel grid.
[in] | iterations | the number of dilation iterations |
Definition at line 479 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::dilation_iteration_num_.
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Set the voxel size for the voxel grid.
[in] | voxel_size | the edge length of a cubic voxel in the voxel grid |
Definition at line 465 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::voxel_size_.
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Set the distinct cloud used for the DISTINCT_CLOUD upsampling method.
Definition at line 411 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::distinct_cloud_.
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Set the maximum number of threads to use.
threads | the maximum number of hardware threads to use (0 sets the value to 1) |
Definition at line 522 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::threads_.
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Set the parameter that specifies the desired number of points within the search radius.
[in] | desired_num_points_in_radius | the desired number of points in the output cloud in a sphere of radius search_radius_ around each point |
Definition at line 451 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::desired_num_points_in_radius_.
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Sets whether the surface and normal are approximated using a polynomial, or only via tangent estimation.
[in] | polynomial_fit | set to true for polynomial fit |
Definition at line 361 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::order_.
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Set the order of the polynomial to be fit.
[in] | order | the order of the polynomial |
Definition at line 350 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::order_.
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Set the method to be used when projection the point on to the MLS surface.
method |
Definition at line 504 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::projection_method_.
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Provide a pointer to the search object.
[in] | tree | a pointer to the spatial search object. |
Definition at line 331 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::search_method_, and pcl::MovingLeastSquares< PointInT, PointOutT >::tree_.
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Set the sphere radius that is to be used for determining the k-nearest neighbors used for fitting.
[in] | radius | the sphere radius that is to contain all k-nearest neighbors |
Definition at line 386 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::search_radius_, and pcl::MovingLeastSquares< PointInT, PointOutT >::sqr_gauss_param_.
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Set the parameter used for distance based weighting of neighbors (the square of the search radius works best in general).
[in] | sqr_gauss_param | the squared Gaussian parameter |
Definition at line 397 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::sqr_gauss_param_.
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Set the upsampling method to be used.
method |
Definition at line 407 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::upsample_method_.
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Set the radius of the circle in the local point plane that will be sampled.
[in] | radius | the radius of the circle |
Definition at line 423 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::upsampling_radius_.
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Set the step size for the local plane sampling.
[in] | step_size | the step size |
Definition at line 436 of file mls.h.
References pcl::MovingLeastSquares< PointInT, PointOutT >::upsampling_step_.
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True if the mls results for the input cloud should be stored.
Definition at line 585 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getCacheMLSResults(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setCacheMLSResults().
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Parameter that specifies whether the normals should be computed for the input cloud or not.
Definition at line 562 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::setComputeNormals().
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Collects for each point in output the corrseponding point in the input.
Definition at line 666 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getCorrespondingIndices().
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Parameter that specifies the desired number of points within the search radius.
Definition at line 580 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getPointDensity(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setPointDensity().
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Number of dilation steps for the VOXEL_GRID_DILATION upsampling method.
Definition at line 660 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getDilationIterations(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setDilationIterations().
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The distinct point cloud that will be projected to the MLS surface.
Definition at line 544 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getDistinctCloud(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setDistinctCloud().
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Stores the MLS result for each point in the input cloud.
Definition at line 590 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getMLSResults().
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The order of the polynomial to be fit.
Definition at line 553 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getPolynomialFit(), pcl::MovingLeastSquares< PointInT, PointOutT >::getPolynomialOrder(), pcl::MovingLeastSquares< PointInT, PointOutT >::setPolynomialFit(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setPolynomialOrder().
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Parameter that specifies the projection method to be used.
Definition at line 593 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getProjectionMethod(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setProjectionMethod().
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The search method template for indices.
Definition at line 547 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::searchForNeighbors(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setSearchMethod().
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The nearest neighbors search radius for each point.
Definition at line 556 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getSearchRadius(), pcl::MovingLeastSquares< PointInT, PointOutT >::searchForNeighbors(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setSearchRadius().
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Parameter for distance based weighting of neighbors (search_radius_ * search_radius_ works fine)
Definition at line 559 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getSqrGaussParam(), pcl::MovingLeastSquares< PointInT, PointOutT >::setSearchRadius(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setSqrGaussParam().
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The maximum number of threads the scheduler should use.
Definition at line 596 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::setNumberOfThreads().
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A pointer to the spatial search object.
Definition at line 550 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getSearchMethod(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setSearchMethod().
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Parameter that specifies the upsampling method to be used.
Definition at line 565 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::setUpsamplingMethod().
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Radius of the circle in the local point plane that will be sampled.
Definition at line 570 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getUpsamplingRadius(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setUpsamplingRadius().
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Step size for the local plane sampling.
Definition at line 575 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getUpsamplingStepSize(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setUpsamplingStepSize().
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Voxel size for the VOXEL_GRID_DILATION upsampling method.
Definition at line 657 of file mls.h.
Referenced by pcl::MovingLeastSquares< PointInT, PointOutT >::getDilationVoxelSize(), and pcl::MovingLeastSquares< PointInT, PointOutT >::setDilationVoxelSize().