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. | |
| ~MovingLeastSquares () override=default | |
| Empty destructor. | |
| void | setComputeNormals (bool compute_normals) |
| Set whether the algorithm should also store the normals computed. | |
| void | setSearchMethod (const KdTreePtr &tree) |
| Provide a pointer to the search object. | |
| KdTreePtr | getSearchMethod () const |
| Get a pointer to the search method used. | |
| void | setPolynomialOrder (int order) |
| Set the order of the polynomial to be fit. | |
| int | getPolynomialOrder () const |
| Get the order of the polynomial to be fit. | |
| void | setSearchRadius (double radius) |
| Set the sphere radius that is to be used for determining the k-nearest neighbors used for fitting. | |
| double | getSearchRadius () const |
| Get the sphere radius used for determining the k-nearest neighbors. | |
| 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). | |
| double | getSqrGaussParam () const |
| Get the parameter for distance based weighting of neighbors. | |
| void | setUpsamplingMethod (UpsamplingMethod method) |
| Set the upsampling method to be used. | |
| void | setDistinctCloud (PointCloudInConstPtr distinct_cloud) |
| Set the distinct cloud used for the DISTINCT_CLOUD upsampling method. | |
| PointCloudInConstPtr | getDistinctCloud () const |
| Get the distinct cloud used for the DISTINCT_CLOUD upsampling method. | |
| void | setUpsamplingRadius (double radius) |
| Set the radius of the circle in the local point plane that will be sampled. | |
| double | getUpsamplingRadius () const |
| Get the radius of the circle in the local point plane that will be sampled. | |
| void | setUpsamplingStepSize (double step_size) |
| Set the step size for the local plane sampling. | |
| double | getUpsamplingStepSize () const |
| Get the step size for the local plane sampling. | |
| void | setPointDensity (int desired_num_points_in_radius) |
| Set the parameter that specifies the desired number of points within the search radius. | |
| int | getPointDensity () const |
| Get the parameter that specifies the desired number of points within the search radius. | |
| void | setDilationVoxelSize (float voxel_size) |
| Set the voxel size for the voxel grid. | |
| float | getDilationVoxelSize () const |
| Get the voxel size for the voxel grid. | |
| void | setDilationIterations (int iterations) |
| Set the number of dilation steps of the voxel grid. | |
| int | getDilationIterations () const |
| Get the number of dilation steps of the voxel grid. | |
| void | setCacheMLSResults (bool cache_mls_results) |
| Set whether the mls results should be stored for each point in the input cloud. | |
| bool | getCacheMLSResults () const |
| Get the cache_mls_results_ value (True if the mls results should be stored, otherwise false). | |
| void | setProjectionMethod (MLSResult::ProjectionMethod method) |
| Set the method to be used when projection the point on to the MLS surface. | |
| MLSResult::ProjectionMethod | getProjectionMethod () const |
| Get the current projection method being used. | |
| const std::vector< MLSResult > & | getMLSResults () const |
| Get the MLSResults for input cloud. | |
| void | setNumberOfThreads (unsigned int threads=1) |
| Set the maximum number of threads to use. | |
| void | process (PointCloudOut &output) override |
| Base method for surface reconstruction for all points given in <setInputCloud (), setIndices ()> | |
| PointIndicesPtr | getCorrespondingIndices () const |
| Get the set of indices with each point in output having the corresponding point in input. | |
| Public Member Functions inherited from pcl::CloudSurfaceProcessing< PointInT, PointOutT > | |
| CloudSurfaceProcessing () | |
| Constructor. | |
| ~CloudSurfaceProcessing () override=default | |
| Empty destructor. | |
| Public Member Functions inherited from pcl::PCLBase< PointInT > | |
| PCLBase () | |
| Empty constructor. | |
| PCLBase (const PCLBase &base) | |
| Copy constructor. | |
| virtual | ~PCLBase ()=default |
| Destructor. | |
| virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
| Provide a pointer to the input dataset. | |
| PointCloudConstPtr const | getInputCloud () const |
| Get a pointer to the input point cloud dataset. | |
| virtual void | setIndices (const IndicesPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. | |
| virtual void | setIndices (const IndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. | |
| virtual void | setIndices (const PointIndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. | |
| 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. | |
| IndicesPtr | getIndices () |
| Get a pointer to the vector of indices used. | |
| IndicesConstPtr const | getIndices () const |
| Get a pointer to the vector of indices used. | |
| const PointInT & | operator[] (std::size_t pos) const |
| Override PointCloud operator[] to shorten code. | |
Protected Member Functions | |
| int | searchForNeighbors (pcl::index_t index, pcl::Indices &indices, std::vector< float > &sqr_distances) const |
| Search for the nearest neighbors of a given point using a radius search. | |
| void | computeMLSPointNormal (pcl::index_t index, const pcl::Indices &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. | |
| void | addProjectedPointNormal (pcl::index_t 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 adding projected points. | |
| void | copyMissingFields (const PointInT &point_in, PointOutT &point_out) const |
| void | performProcessing (PointCloudOut &output) override |
| Abstract surface reconstruction method. | |
| void | performUpsampling (PointCloudOut &output) |
| Perform upsampling for the distinct-cloud and voxel-grid methods. | |
| Protected Member Functions inherited from pcl::PCLBase< PointInT > | |
| bool | initCompute () |
| This method should get called before starting the actual computation. | |
| bool | deinitCompute () |
| This method should get called after finishing the actual computation. | |
Protected Attributes | |
| NormalCloudPtr | normals_ {nullptr} |
| The point cloud that will hold the estimated normals, if set. | |
| PointCloudInConstPtr | distinct_cloud_ {nullptr} |
| The distinct point cloud that will be projected to the MLS surface. | |
| SearchMethod | search_method_ |
| The search method template for indices. | |
| KdTreePtr | tree_ {nullptr} |
| A pointer to the spatial search object. | |
| int | order_ {2} |
| The order of the polynomial to be fit. | |
| double | search_radius_ {0.0} |
| The nearest neighbors search radius for each point. | |
| double | sqr_gauss_param_ {0.0} |
| Parameter for distance based weighting of neighbors (search_radius_ * search_radius_ works fine) | |
| bool | compute_normals_ {false} |
| Parameter that specifies whether the normals should be computed for the input cloud or not. | |
| UpsamplingMethod | upsample_method_ |
| Parameter that specifies the upsampling method to be used. | |
| double | upsampling_radius_ {0.0} |
| Radius of the circle in the local point plane that will be sampled. | |
| double | upsampling_step_ {0.0} |
| Step size for the local plane sampling. | |
| int | desired_num_points_in_radius_ {0} |
| Parameter that specifies the desired number of points within the search radius. | |
| bool | cache_mls_results_ {true} |
| True if the mls results for the input cloud should be stored. | |
| std::vector< MLSResult > | mls_results_ {} |
| Stores the MLS result for each point in the input cloud. | |
| MLSResult::ProjectionMethod | projection_method_ {MLSResult::SIMPLE} |
| Parameter that specifies the projection method to be used. | |
| unsigned int | threads_ {1} |
| The maximum number of threads the scheduler should use. | |
| float | voxel_size_ {1.0f} |
| Voxel size for the VOXEL_GRID_DILATION upsampling method. | |
| int | dilation_iteration_num_ {0} |
| Number of dilation steps for the VOXEL_GRID_DILATION upsampling method. | |
| int | nr_coeff_ {0} |
| Number of coefficients, to be computed from the requested order. | |
| PointIndicesPtr | corresponding_input_indices_ {nullptr} |
| Collects for each point in output the corresponding point in the input. | |
| Protected Attributes inherited from pcl::PCLBase< PointInT > | |
| PointCloudConstPtr | input_ |
| The input point cloud dataset. | |
| IndicesPtr | indices_ |
| A pointer to the vector of point indices to use. | |
| bool | use_indices_ |
| Set to true if point indices are used. | |
| bool | fake_indices_ |
| If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. | |
Detailed Description
class pcl::MovingLeastSquares< PointInT, PointOutT >
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
- Note
- There is a parallelized version of the processing step, using the OpenMP standard. Compared to the standard version, an overhead is incurred in terms of runtime and memory usage. The upsampling methods DISTINCT_CLOUD and VOXEL_GRID_DILATION are not parallelized completely, i.e. parts of the algorithm run on a single thread only.
Member Typedef Documentation
◆ ConstPtr
| using pcl::MovingLeastSquares< PointInT, PointOutT >::ConstPtr = shared_ptr<const MovingLeastSquares<PointInT, PointOutT> > |
◆ KdTree
| using pcl::MovingLeastSquares< PointInT, PointOutT >::KdTree = pcl::search::Search<PointInT> |
◆ KdTreePtr
| using pcl::MovingLeastSquares< PointInT, PointOutT >::KdTreePtr = typename KdTree::Ptr |
◆ NormalCloud
| using pcl::MovingLeastSquares< PointInT, PointOutT >::NormalCloud = pcl::PointCloud<pcl::Normal> |
◆ NormalCloudPtr
| using pcl::MovingLeastSquares< PointInT, PointOutT >::NormalCloudPtr = NormalCloud::Ptr |
◆ PointCloudIn
| using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudIn = pcl::PointCloud<PointInT> |
◆ PointCloudInConstPtr
| using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudInConstPtr = typename PointCloudIn::ConstPtr |
◆ PointCloudInPtr
| using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudInPtr = typename PointCloudIn::Ptr |
◆ PointCloudOut
| using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudOut = pcl::PointCloud<PointOutT> |
◆ PointCloudOutConstPtr
| using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudOutConstPtr = typename PointCloudOut::ConstPtr |
◆ PointCloudOutPtr
| using pcl::MovingLeastSquares< PointInT, PointOutT >::PointCloudOutPtr = typename PointCloudOut::Ptr |
◆ Ptr
| using pcl::MovingLeastSquares< PointInT, PointOutT >::Ptr = shared_ptr<MovingLeastSquares<PointInT, PointOutT> > |
◆ SearchMethod
| using pcl::MovingLeastSquares< PointInT, PointOutT >::SearchMethod = std::function<int (pcl::index_t, double, pcl::Indices &, std::vector<float> &)> |
Member Enumeration Documentation
◆ UpsamplingMethod
| enum pcl::MovingLeastSquares::UpsamplingMethod |
| Enumerator | |
|---|---|
| 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. |
Constructor & Destructor Documentation
◆ MovingLeastSquares()
|
inline |
Empty constructor.
Definition at line 297 of file mls.h.
References pcl::CloudSurfaceProcessing< PointInT, PointOutT >::CloudSurfaceProcessing(), distinct_cloud_, NONE, tree_, and upsample_method_.
◆ ~MovingLeastSquares()
|
overridedefault |
Empty destructor.
Member Function Documentation
◆ addProjectedPointNormal()
|
protected |
This is a helper function for adding projected points.
- Parameters
-
[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 254 of file mls.hpp.
References compute_normals_, copyMissingFields(), pcl::_Normal::curvature, pcl::PointIndices::indices, pcl::PCLBase< PointInT >::input_, and pcl::PointCloud< PointT >::push_back().
Referenced by computeMLSPointNormal(), and performUpsampling().
◆ computeMLSPointNormal()
|
protected |
Smooth a given point and its neighborghood using Moving Least Squares.
- Parameters
-
[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 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 176 of file mls.hpp.
References addProjectedPointNormal(), pcl::MLSResult::computeMLSSurface(), pcl::MLSResult::curvature, desired_num_points_in_radius_, pcl::PCLBase< PointInT >::input_, NONE, pcl::MLSResult::MLSProjectionResults::normal, nr_coeff_, pcl::MLSResult::num_neighbors, order_, pcl::MLSResult::MLSProjectionResults::point, projection_method_, pcl::MLSResult::projectPointSimpleToPolynomialSurface(), pcl::MLSResult::projectPointToMLSPlane(), pcl::MLSResult::projectQueryPoint(), RANDOM_UNIFORM_DENSITY, SAMPLE_LOCAL_PLANE, search_radius_, upsample_method_, upsampling_radius_, and upsampling_step_.
Referenced by performProcessing().
◆ copyMissingFields()
|
protected |
Definition at line 866 of file mls.hpp.
References pcl::copyPoint().
Referenced by addProjectedPointNormal(), and performProcessing().
◆ getCacheMLSResults()
|
inline |
Get the cache_mls_results_ value (True if the mls results should be stored, otherwise false).
Definition at line 461 of file mls.h.
References cache_mls_results_.
◆ getCorrespondingIndices()
|
inline |
Get the set of indices with each point in output having the corresponding point in input.
Definition at line 501 of file mls.h.
References corresponding_input_indices_.
◆ getDilationIterations()
|
inline |
Get the number of dilation steps of the voxel grid.
- Note
- Used only in the VOXEL_GRID_DILATION upsampling method
Definition at line 449 of file mls.h.
References dilation_iteration_num_.
◆ getDilationVoxelSize()
|
inline |
Get the voxel size for the voxel grid.
- Note
- Used only in the VOXEL_GRID_DILATION upsampling method
Definition at line 436 of file mls.h.
References voxel_size_.
◆ getDistinctCloud()
|
inline |
Get the distinct cloud used for the DISTINCT_CLOUD upsampling method.
Definition at line 379 of file mls.h.
References distinct_cloud_.
◆ getMLSResults()
|
inline |
Get the MLSResults for input cloud.
- Note
- The results are only stored if setCacheMLSResults(true) was called or when using the upsampling method DISTINCT_CLOUD or VOXEL_GRID_DILATION.
- This vector is aligned with the input cloud indices, so use getCorrespondingIndices to get the correct results when using output cloud indices.
Definition at line 480 of file mls.h.
References mls_results_.
◆ getPointDensity()
|
inline |
Get the parameter that specifies the desired number of points within the search radius.
- Note
- Used only in the case of RANDOM_UNIFORM_DENSITY upsampling
Definition at line 422 of file mls.h.
References desired_num_points_in_radius_.
◆ getPolynomialOrder()
|
inline |
◆ getProjectionMethod()
|
inline |
Get the current projection method being used.
Definition at line 473 of file mls.h.
References projection_method_.
◆ getSearchMethod()
|
inline |
◆ getSearchRadius()
|
inline |
Get the sphere radius used for determining the k-nearest neighbors.
Definition at line 354 of file mls.h.
References search_radius_.
◆ getSqrGaussParam()
|
inline |
Get the parameter for distance based weighting of neighbors.
Definition at line 365 of file mls.h.
References sqr_gauss_param_.
◆ getUpsamplingRadius()
|
inline |
Get the radius of the circle in the local point plane that will be sampled.
- Note
- Used only in the case of SAMPLE_LOCAL_PLANE upsampling
Definition at line 393 of file mls.h.
References upsampling_radius_.
◆ getUpsamplingStepSize()
|
inline |
Get the step size for the local plane sampling.
- Note
- Used only in the case of SAMPLE_LOCAL_PLANE upsampling
Definition at line 407 of file mls.h.
References upsampling_step_.
◆ performProcessing()
|
overrideprotectedvirtual |
Abstract surface reconstruction method.
- Parameters
-
[out] output the result of the reconstruction
Implements pcl::CloudSurfaceProcessing< PointInT, PointOutT >.
Definition at line 286 of file mls.hpp.
References pcl::PointCloud< PointT >::begin(), cache_mls_results_, compute_normals_, computeMLSPointNormal(), copyMissingFields(), corresponding_input_indices_, pcl::PointCloud< PointT >::end(), pcl::PCLBase< PointInT >::indices_, pcl::PCLBase< PointInT >::input_, pcl::PointCloud< PointT >::insert(), mls_results_, normals_, nr_coeff_, order_, performUpsampling(), searchForNeighbors(), pcl::PointCloud< PointT >::size(), and threads_.
Referenced by process().
◆ performUpsampling()
|
protected |
Perform upsampling for the distinct-cloud and voxel-grid methods.
- Parameters
-
[out] output the result of the reconstruction
Definition at line 372 of file mls.hpp.
References addProjectedPointNormal(), corresponding_input_indices_, pcl::MovingLeastSquares< PointInT, PointOutT >::MLSVoxelGrid::dilate(), dilation_iteration_num_, DISTINCT_CLOUD, distinct_cloud_, pcl::MovingLeastSquares< PointInT, PointOutT >::MLSVoxelGrid::getPosition(), pcl::PCLBase< PointInT >::indices_, pcl::PCLBase< PointInT >::input_, mls_results_, pcl::MLSResult::MLSProjectionResults::normal, normals_, nr_coeff_, pcl::MLSResult::MLSProjectionResults::point, projection_method_, tree_, upsample_method_, pcl::MovingLeastSquares< PointInT, PointOutT >::MLSVoxelGrid::voxel_grid_, VOXEL_GRID_DILATION, and voxel_size_.
Referenced by performProcessing().
◆ process()
|
overridevirtual |
Base method for surface reconstruction for all points given in <setInputCloud (), setIndices ()>
- Parameters
-
[out] output the resultant reconstructed surface model
Reimplemented from pcl::CloudSurfaceProcessing< PointInT, PointOutT >.
Definition at line 63 of file mls.hpp.
References cache_mls_results_, pcl::PointCloud< PointT >::clear(), compute_normals_, corresponding_input_indices_, pcl::PCLBase< PointInT >::deinitCompute(), DISTINCT_CLOUD, distinct_cloud_, pcl::for_each_type(), pcl::PointCloud< PointT >::header, pcl::PointCloud< PointT >::height, pcl::PCLBase< PointInT >::initCompute(), pcl::PCLBase< PointInT >::input_, mls_results_, normals_, performProcessing(), RANDOM_UNIFORM_DENSITY, search_radius_, setSearchMethod(), pcl::PointCloud< PointT >::size(), sqr_gauss_param_, tree_, upsample_method_, VOXEL_GRID_DILATION, and pcl::PointCloud< PointT >::width.
◆ searchForNeighbors()
|
inlineprotected |
Search for the nearest neighbors of a given point using a radius search.
- Parameters
-
[in] index the index of the query point [out] indices the resultant vector of indices representing the neighbors within search_radius_ [out] sqr_distances the resultant squared distances from the query point to the neighbors within search_radius_
Definition at line 639 of file mls.h.
References search_method_, and search_radius_.
Referenced by performProcessing().
◆ setCacheMLSResults()
|
inline |
Set whether the mls results should be stored for each point in the input cloud.
- Parameters
-
[in] cache_mls_results True if the mls results should be stored, otherwise false.
- Note
- The cache_mls_results_ is forced to be true when using upsampling method VOXEL_GRID_DILATION or DISTINCT_CLOUD.
- If memory consumption is a concern, then set it to false when not using upsampling method VOXEL_GRID_DILATION or DISTINCT_CLOUD.
Definition at line 457 of file mls.h.
References cache_mls_results_.
◆ setComputeNormals()
|
inline |
Set whether the algorithm should also store the normals computed.
- Note
- This is optional, but need a proper output cloud type
Definition at line 314 of file mls.h.
References compute_normals_.
◆ setDilationIterations()
|
inline |
Set the number of dilation steps of the voxel grid.
- Note
- Used only in the VOXEL_GRID_DILATION upsampling method
- Parameters
-
[in] iterations the number of dilation iterations
Definition at line 443 of file mls.h.
References dilation_iteration_num_.
◆ setDilationVoxelSize()
|
inline |
Set the voxel size for the voxel grid.
- Note
- Used only in the VOXEL_GRID_DILATION upsampling method
- Parameters
-
[in] voxel_size the edge length of a cubic voxel in the voxel grid
Definition at line 429 of file mls.h.
References voxel_size_.
◆ setDistinctCloud()
|
inline |
Set the distinct cloud used for the DISTINCT_CLOUD upsampling method.
Definition at line 375 of file mls.h.
References distinct_cloud_.
◆ setNumberOfThreads()
|
inline |
◆ setPointDensity()
|
inline |
Set the parameter that specifies the desired number of points within the search radius.
- Note
- Used only in the case of RANDOM_UNIFORM_DENSITY upsampling
- Parameters
-
[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 415 of file mls.h.
References desired_num_points_in_radius_.
◆ setPolynomialOrder()
|
inline |
◆ setProjectionMethod()
|
inline |
Set the method to be used when projection the point on to the MLS surface.
- Parameters
-
method
- Note
- This is only used when polynomial fit is enabled.
Definition at line 468 of file mls.h.
References projection_method_.
◆ setSearchMethod()
|
inline |
Provide a pointer to the search object.
- Parameters
-
[in] tree a pointer to the spatial search object.
Definition at line 320 of file mls.h.
References search_method_, and tree_.
Referenced by process().
◆ setSearchRadius()
|
inline |
Set the sphere radius that is to be used for determining the k-nearest neighbors used for fitting.
- Parameters
-
[in] radius the sphere radius that is to contain all k-nearest neighbors
- Note
- Calling this method resets the squared Gaussian parameter to radius * radius !
Definition at line 350 of file mls.h.
References search_radius_, and sqr_gauss_param_.
◆ setSqrGaussParam()
|
inline |
Set the parameter used for distance based weighting of neighbors (the square of the search radius works best in general).
- Parameters
-
[in] sqr_gauss_param the squared Gaussian parameter
Definition at line 361 of file mls.h.
References sqr_gauss_param_.
◆ setUpsamplingMethod()
|
inline |
Set the upsampling method to be used.
- Parameters
-
method
Definition at line 371 of file mls.h.
References upsample_method_.
◆ setUpsamplingRadius()
|
inline |
Set the radius of the circle in the local point plane that will be sampled.
- Note
- Used only in the case of SAMPLE_LOCAL_PLANE upsampling
- Parameters
-
[in] radius the radius of the circle
Definition at line 387 of file mls.h.
References upsampling_radius_.
◆ setUpsamplingStepSize()
|
inline |
Set the step size for the local plane sampling.
- Note
- Used only in the case of SAMPLE_LOCAL_PLANE upsampling
- Parameters
-
[in] step_size the step size
Definition at line 400 of file mls.h.
References upsampling_step_.
Member Data Documentation
◆ cache_mls_results_
|
protected |
True if the mls results for the input cloud should be stored.
- Note
- This is forced to be true when using upsampling methods VOXEL_GRID_DILATION or DISTINCT_CLOUD.
Definition at line 549 of file mls.h.
Referenced by getCacheMLSResults(), performProcessing(), process(), and setCacheMLSResults().
◆ compute_normals_
|
protected |
Parameter that specifies whether the normals should be computed for the input cloud or not.
Definition at line 526 of file mls.h.
Referenced by addProjectedPointNormal(), performProcessing(), process(), and setComputeNormals().
◆ corresponding_input_indices_
|
protected |
Collects for each point in output the corresponding point in the input.
Definition at line 631 of file mls.h.
Referenced by getCorrespondingIndices(), performProcessing(), performUpsampling(), and process().
◆ desired_num_points_in_radius_
|
protected |
Parameter that specifies the desired number of points within the search radius.
- Note
- Used only in the case of RANDOM_UNIFORM_DENSITY upsampling
Definition at line 544 of file mls.h.
Referenced by computeMLSPointNormal(), getPointDensity(), and setPointDensity().
◆ dilation_iteration_num_
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protected |
Number of dilation steps for the VOXEL_GRID_DILATION upsampling method.
Definition at line 625 of file mls.h.
Referenced by getDilationIterations(), performUpsampling(), and setDilationIterations().
◆ distinct_cloud_
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protected |
The distinct point cloud that will be projected to the MLS surface.
Definition at line 508 of file mls.h.
Referenced by getDistinctCloud(), MovingLeastSquares(), performUpsampling(), process(), and setDistinctCloud().
◆ mls_results_
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protected |
Stores the MLS result for each point in the input cloud.
- Note
- Used only in the case of VOXEL_GRID_DILATION or DISTINCT_CLOUD upsampling
Definition at line 554 of file mls.h.
Referenced by getMLSResults(), performProcessing(), performUpsampling(), and process().
◆ normals_
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protected |
The point cloud that will hold the estimated normals, if set.
Definition at line 505 of file mls.h.
Referenced by performProcessing(), performUpsampling(), and process().
◆ nr_coeff_
|
protected |
Number of coefficients, to be computed from the requested order.
Definition at line 628 of file mls.h.
Referenced by computeMLSPointNormal(), performProcessing(), and performUpsampling().
◆ order_
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protected |
The order of the polynomial to be fit.
Definition at line 517 of file mls.h.
Referenced by computeMLSPointNormal(), getPolynomialOrder(), performProcessing(), and setPolynomialOrder().
◆ projection_method_
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protected |
Parameter that specifies the projection method to be used.
Definition at line 557 of file mls.h.
Referenced by computeMLSPointNormal(), getProjectionMethod(), performUpsampling(), and setProjectionMethod().
◆ search_method_
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protected |
The search method template for indices.
Definition at line 511 of file mls.h.
Referenced by searchForNeighbors(), and setSearchMethod().
◆ search_radius_
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protected |
The nearest neighbors search radius for each point.
Definition at line 520 of file mls.h.
Referenced by computeMLSPointNormal(), getSearchRadius(), process(), searchForNeighbors(), and setSearchRadius().
◆ sqr_gauss_param_
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protected |
Parameter for distance based weighting of neighbors (search_radius_ * search_radius_ works fine)
Definition at line 523 of file mls.h.
Referenced by getSqrGaussParam(), process(), setSearchRadius(), and setSqrGaussParam().
◆ threads_
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protected |
The maximum number of threads the scheduler should use.
Definition at line 560 of file mls.h.
Referenced by performProcessing(), and setNumberOfThreads().
◆ tree_
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protected |
A pointer to the spatial search object.
Definition at line 514 of file mls.h.
Referenced by getSearchMethod(), MovingLeastSquares(), performUpsampling(), process(), and setSearchMethod().
◆ upsample_method_
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protected |
Parameter that specifies the upsampling method to be used.
Definition at line 529 of file mls.h.
Referenced by computeMLSPointNormal(), MovingLeastSquares(), performUpsampling(), process(), and setUpsamplingMethod().
◆ upsampling_radius_
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protected |
Radius of the circle in the local point plane that will be sampled.
- Note
- Used only in the case of SAMPLE_LOCAL_PLANE upsampling
Definition at line 534 of file mls.h.
Referenced by computeMLSPointNormal(), getUpsamplingRadius(), and setUpsamplingRadius().
◆ upsampling_step_
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protected |
Step size for the local plane sampling.
- Note
- Used only in the case of SAMPLE_LOCAL_PLANE upsampling
Definition at line 539 of file mls.h.
Referenced by computeMLSPointNormal(), getUpsamplingStepSize(), and setUpsamplingStepSize().
◆ voxel_size_
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protected |
Voxel size for the VOXEL_GRID_DILATION upsampling method.
Definition at line 622 of file mls.h.
Referenced by getDilationVoxelSize(), performUpsampling(), and setDilationVoxelSize().
The documentation for this class was generated from the following files: