Point Cloud Library (PCL)
1.10.0
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47 #include <pcl/pcl_base.h>
49 #include <pcl/search/pcl_search.h>
52 #include <pcl/surface/boost.h>
53 #include <pcl/surface/eigen.h>
54 #include <pcl/surface/processing.h>
96 MLSResult (
const Eigen::Vector3d &a_query_point,
97 const Eigen::Vector3d &a_mean,
98 const Eigen::Vector3d &a_plane_normal,
99 const Eigen::Vector3d &a_u,
100 const Eigen::Vector3d &a_v,
101 const Eigen::VectorXd &a_c_vec,
102 const int a_num_neighbors,
103 const float a_curvature,
113 getMLSCoordinates (
const Eigen::Vector3d &pt,
double &u,
double &v,
double &w)
const;
136 inline PolynomialPartialDerivative
145 inline Eigen::Vector2f
157 inline MLSProjectionResults
165 inline MLSProjectionResults
174 inline MLSProjectionResults
186 inline MLSProjectionResults
197 inline MLSProjectionResults
207 template <
typename Po
intT>
void
210 const std::vector<int> &nn_indices,
211 double search_radius,
212 int polynomial_order = 2,
213 std::function<
double(
const double)> weight_func = {});
234 double computeMLSWeight (
const double sq_dist,
const double sq_mls_radius) {
return (std::exp (-sq_dist / sq_mls_radius)); }
251 template <
typename Po
intInT,
typename Po
intOutT>
277 using SearchMethod = std::function<int (
int,
double, std::vector<int> &, std::vector<float> &)>;
314 rng_uniform_distribution_ ()
335 search_method_ = [
this] (
int index,
double radius, std::vector<int>& k_indices, std::vector<float>& k_sqr_distances)
337 return tree_->radiusSearch (index, radius, k_indices, k_sqr_distances, 0);
359 [[deprecated(
"use setPolynomialOrder() instead")]]
377 [[deprecated(
"use getPolynomialOrder() instead")]]
515 inline const std::vector<MLSResult>&
626 index_3d[1] = static_cast<Eigen::Vector3i::Scalar> (index_1d /
data_size_);
628 index_3d[2] = static_cast<Eigen::Vector3i::Scalar> (index_1d);
634 for (
int i = 0; i < 3; ++i)
641 Eigen::Vector3i index_3d;
643 for (
int i = 0; i < 3; ++i)
647 typedef std::map<std::uint64_t, Leaf>
HashMap;
692 const std::vector<int> &nn_indices,
710 const Eigen::Vector3d &point,
711 const Eigen::Vector3d &normal,
720 PointOutT &point_out)
const;
736 mutable std::mt19937 rng_;
741 std::unique_ptr<std::uniform_real_distribution<>> rng_uniform_distribution_;
745 getClassName ()
const {
return (
"MovingLeastSquares"); }
748 template <
typename Po
intInT,
typename Po
intOutT>
752 #ifdef PCL_NO_PRECOMPILE
753 #include <pcl/surface/impl/mls.hpp>
void setDilationIterations(int iterations)
Set the number of dilation steps of the voxel grid.
int num_neighbors
The number of neighbors used to create the mls surface.
MLSProjectionResults projectPointOrthogonalToPolynomialSurface(const double u, const double v, const double w) const
Project a point orthogonal to the polynomial surface.
Eigen::Vector3d mean
The mean point of all the neighbors.
MLSProjectionResults projectPointToMLSPlane(const double u, const double v) const
Project a point onto the MLS plane.
Defines all the PCL and non-PCL macros used.
MLSResult::ProjectionMethod projection_method_
Parameter that specifies the projection method to be used.
int getPolynomialOrder() const
Get the order of the polynomial to be fit.
This file defines compatibility wrappers for low level I/O functions.
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.
int dilation_iteration_num_
Number of dilation steps for the VOXEL_GRID_DILATION upsampling method.
PointIndices::Ptr PointIndicesPtr
void setComputeNormals(bool compute_normals)
Set whether the algorithm should also store the normals computed.
shared_ptr< Indices > IndicesPtr
PointCloudInConstPtr getDistinctCloud() const
Get the distinct cloud used for the DISTINCT_CLOUD upsampling method.
void setUpsamplingMethod(UpsamplingMethod method)
Set the upsampling method to be used.
void getCellIndex(const Eigen::Vector3f &p, Eigen::Vector3i &index) const
~MovingLeastSquares()
Empty destructor.
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.
void setPolynomialOrder(int order)
Set the order of the polynomial to be fit.
typename PointCloudOut::ConstPtr PointCloudOutConstPtr
double z_uu
The partial derivative d^2z/du^2.
MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data s...
std::function< int(int, double, std::vector< int > &, std::vector< float > &)> SearchMethod
A minimalistic implementation of a voxel grid, necessary for the point cloud upsampling.
double sqr_gauss_param_
Parameter for distance based weighting of neighbors (search_radius_ * search_radius_ works fine)
double u
The u-coordinate of the projected point in local MLS frame.
MLSVoxelGrid(PointCloudInConstPtr &cloud, IndicesPtr &indices, float voxel_size)
void setUpsamplingRadius(double radius)
Set the radius of the circle in the local point plane that will be sampled.
float curvature
The curvature at the query point.
bool getPolynomialFit() const
Get the polynomial_fit value (true if the surface and normal are approximated using a polynomial).
typename PointCloudIn::ConstPtr PointCloudInConstPtr
int getPointDensity() const
Get the parameter that specifies the desired number of points within the search radius.
MLSResult::ProjectionMethod getProjectionMethod() const
Get the current projection method being used.
void copyMissingFields(const PointInT &point_in, PointOutT &point_out) const
Eigen::Vector3d point
The projected point.
void setSearchRadius(double radius)
Set the sphere radius that is to be used for determining the k-nearest neighbors used for fitting.
MovingLeastSquares()
Empty constructor.
Eigen::Vector3d normal
The projected point's normal.
Eigen::VectorXd c_vec
The polynomial coefficients Example: z = c_vec[0] + c_vec[1]*v + c_vec[2]*v^2 + c_vec[3]*u + c_vec[4]...
Eigen::Vector4f bounding_max_
PointCloud represents the base class in PCL for storing collections of 3D points.
double z_vv
The partial derivative d^2z/dv^2.
double upsampling_radius_
Radius of the circle in the local point plane that will be sampled.
shared_ptr< const MovingLeastSquares< PointInT, PointOutT > > ConstPtr
No upsampling will be done, only the input points will be projected to their own MLS surfaces.
std::vector< MLSResult > mls_results_
Stores the MLS result for each point in the input cloud.
Eigen::Vector3d query_point
The query point about which the mls surface was generated.
Project along the mls plane normal to the polynomial surface.
pcl::PointCloud< pcl::Normal > NormalCloud
PointCloudInConstPtr distinct_cloud_
The distinct point cloud that will be projected to the MLS surface.
double z_v
The partial derivative dz/dv.
double getSearchRadius() const
Get the sphere radius used for determining the k-nearest neighbors.
void performUpsampling(PointCloudOut &output)
Perform upsampling for the distinct-cloud and voxel-grid methods.
void computeMLSSurface(const pcl::PointCloud< PointT > &cloud, int index, const std::vector< int > &nn_indices, double search_radius, int polynomial_order=2, std::function< double(const double)> weight_func={})
Smooth a given point and its neighborghood using Moving Least Squares.
typename PointCloudIn::Ptr PointCloudInPtr
void getPosition(const std::uint64_t &index_1d, Eigen::Vector3f &point) const
SearchMethod search_method_
The search method template for indices.
Eigen::Vector3d plane_normal
The normal of the local plane of the query point.
Project to the closest point on the polynonomial surface.
void getIndexIn1D(const Eigen::Vector3i &index, std::uint64_t &index_1d) const
Eigen::Vector2f calculatePrincipleCurvatures(const double u, const double v) const
Calculate the principle curvatures using the polynomial surface.
PolynomialPartialDerivative getPolynomialPartialDerivative(const double u, const double v) const
Calculate the polynomial's first and second partial derivatives.
void setPolynomialFit(bool polynomial_fit)
Sets whether the surface and normal are approximated using a polynomial, or only via tangent estimati...
shared_ptr< MovingLeastSquares< PointInT, PointOutT > > Ptr
double v
The u-coordinate of the projected point in local MLS frame.
void setCacheMLSResults(bool cache_mls_results)
Set whether the mls results should be stored for each point in the input cloud.
unsigned int threads_
The maximum number of threads the scheduler should use.
double search_radius_
The nearest neighbors search radius for each point.
Data structure used to store the results of the MLS fitting.
void process(PointCloudOut &output) override
Base method for surface reconstruction for all points given in <setInputCloud (), setIndices ()>
Data structure used to store the MLS polynomial partial derivatives.
bool getCacheMLSResults() const
Get the cache_mls_results_ value (True if the mls results should be stored, otherwise false).
The local plane of each input point will be sampled in a circular fashion using the upsampling_radius...
void setProjectionMethod(MLSResult::ProjectionMethod method)
Set the method to be used when projection the point on to the MLS surface.
bool cache_mls_results_
True if the mls results for the input cloud should be stored.
void setUpsamplingStepSize(double step_size)
Set the step size for the local plane sampling.
double z_u
The partial derivative dz/du.
double z_uv
The partial derivative d^2z/dudv.
shared_ptr< pcl::search::Search< PointInT > > Ptr
CloudSurfaceProcessing represents the base class for algorithms that takes a point cloud as input and...
Project the points of the distinct cloud to the MLS surface.
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
Data structure used to store the MLS projection results.
bool compute_normals_
Parameter that specifies whether the normals should be computed for the input cloud or not.
void getIndexIn3D(std::uint64_t index_1d, Eigen::Vector3i &index_3d) const
double getSqrGaussParam() const
Get the parameter for distance based weighting of neighbors.
KdTreePtr getSearchMethod() const
Get a pointer to the search method used.
int order
The order of the polynomial.
double getUpsamplingStepSize() const
Get the step size for the local plane sampling.
int desired_num_points_in_radius_
Parameter that specifies the desired number of points within the search radius.
typename PointCloudOut::Ptr PointCloudOutPtr
double upsampling_step_
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.
bool valid
If True, the mls results data is valid, otherwise False.
float voxel_size_
Voxel size for the VOXEL_GRID_DILATION upsampling method.
void setDistinctCloud(PointCloudInConstPtr distinct_cloud)
Set the distinct cloud used for the DISTINCT_CLOUD upsampling method.
shared_ptr< PointCloud< pcl::Normal > > Ptr
MLSProjectionResults projectQueryPoint(ProjectionMethod method, int required_neighbors=0) const
Project the query point used to generate the mls surface about using the specified method.
const std::vector< MLSResult > & getMLSResults() const
Get the MLSResults for input cloud.
typename KdTree::Ptr KdTreePtr
Eigen::Vector4f bounding_min_
std::map< std::uint64_t, Leaf > HashMap
Eigen::Vector3d v_axis
The axis corresponding to the v-coordinates of the local plane of the query point.
void performProcessing(PointCloudOut &output) override
Abstract surface reconstruction method.
MLSProjectionResults projectPointSimpleToPolynomialSurface(const double u, const double v) const
Project a point along the MLS plane normal to the polynomial surface.
void setSqrGaussParam(double sqr_gauss_param)
Set the parameter used for distance based weighting of neighbors (the square of the search radius wor...
The local plane of each input point will be sampled using an uniform random distribution such that th...
shared_ptr< const PointCloud< PointOutT > > ConstPtr
void setNumberOfThreads(unsigned int threads=1)
Set the maximum number of threads to use.
double getUpsamplingRadius() const
Get the radius of the circle in the local point plane that will be sampled.
UpsamplingMethod upsample_method_
Parameter that specifies the upsampling method to be used.
double z
The z component of the polynomial evaluated at z(u, v).
MLSProjectionResults projectPoint(const Eigen::Vector3d &pt, ProjectionMethod method, int required_neighbors=0) const
Project a point using the specified method.
int order_
The order of the polynomial to be fit.
PointIndices::Ptr PointIndicesPtr
double getPolynomialValue(const double u, const double v) const
Calculate the polynomial.
KdTreePtr tree_
A pointer to the spatial search object.
int nr_coeff_
Number of coefficients, to be computed from the requested order.
pcl::PointCloud< PointOutT > PointCloudOut
PointIndicesPtr getCorrespondingIndices() const
Get the set of indices with each point in output having the corresponding point in input.
void getMLSCoordinates(const Eigen::Vector3d &pt, double &u, double &v, double &w) const
Given a point calculate it's 3D location in the MLS frame.
void setDilationVoxelSize(float voxel_size)
Set the voxel size for the voxel grid.
Project to the mls plane.
NormalCloudPtr normals_
The point cloud that will hold the estimated normals, if set.
The input cloud will be inserted into a voxel grid with voxels of size voxel_size_; this voxel grid w...
void setSearchMethod(const KdTreePtr &tree)
Provide a pointer to the search object.
NormalCloud::Ptr NormalCloudPtr
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.
float getDilationVoxelSize() const
Get the voxel size for the voxel grid.
boost::shared_ptr< T > shared_ptr
Alias for boost::shared_ptr.
int getDilationIterations() const
Get the number of dilation steps of the voxel grid.
PointIndicesPtr corresponding_input_indices_
Collects for each point in output the corrseponding point in the input.
Eigen::Vector3d u_axis
The axis corresponding to the u-coordinates of the local plane of the query point.