\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 4.6.3 - Point Set Processing
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Point Set Processing Reference

point_set_processing_detail.png
Pierre Alliez, Clément Jamin, Laurent Saboret, Nader Salman, Shihao Wu
This CGAL component implements methods to analyze and process point sets. The input is an unorganized point set, possibly with normal attributes (unoriented or oriented). The point set can be analyzed to measure its average spacing, and processed through functions devised for simplification, regularization, upsampling, outlier removal, smoothing, normal estimation and normal orientation.


Introduced in: CGAL 3.5
Depends on: Eigen
BibTeX: cgal:ass-psp-15b
License: GPL
Windows Demo: See Polyhedral Surface
Common Demo Dlls: dlls

Classified Reference Pages

Functions

Classes

struct  CGAL::value_type_traits< T >
 Class providing the value type of an iterator, and in the case of an output iterator, a type of objects that can be put in it. More...
 

Functions

template<typename Concurrency_tag , typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
double CGAL::bilateral_smooth_point_set (ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, unsigned int k, typename Kernel::FT sharpness_angle, const Kernel &)
 This function smooths an input point set by iteratively projecting each point onto the implicit surface patch fitted over its k nearest neighbors. More...
 
template<typename InputIterator , typename PointPMap , typename Kernel >
Kernel::FT CGAL::compute_average_spacing (InputIterator first, InputIterator beyond, PointPMap point_pmap, unsigned int k, const Kernel &)
 Computes average spacing from k nearest neighbors. More...
 
template<typename OutputIterator , typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
OutputIterator CGAL::edge_aware_upsample_point_set (ForwardIterator first, ForwardIterator beyond, OutputIterator output, PointPMap point_pmap, NormalPMap normal_pmap, const typename Kernel::FT sharpness_angle, typename Kernel::FT edge_sensitivity, typename Kernel::FT neighbor_radius, const unsigned int number_of_output_points, const Kernel &)
 This method progressively upsamples the point set while approaching the edge singularities (detected by normal variation), which generates a denser point set from an input point set. More...
 
template<typename ForwardIterator , typename PointPMap , typename Kernel >
ForwardIterator CGAL::grid_simplify_point_set (ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, double epsilon, const Kernel &)
 Merges points which belong to the same cell of a grid of cell size = epsilon. More...
 
template<typename OutputIteratorValueType , typename OutputIterator , typename PointPMap , typename NormalPMap , typename Kernel >
bool CGAL::read_off_points_and_normals (std::istream &stream, OutputIterator output, PointPMap point_pmap, NormalPMap normal_pmap, const Kernel &)
 Reads points (positions + normals, if available) from a .off ASCII stream. More...
 
template<typename OutputIteratorValueType , typename OutputIterator , typename PointPMap , typename Kernel >
bool CGAL::read_off_points (std::istream &stream, OutputIterator output, PointPMap point_pmap, const Kernel &kernel)
 Reads points (position only) from a .off ASCII stream. More...
 
template<typename OutputIteratorValueType , typename OutputIterator , typename PointPMap , typename NormalPMap , typename Kernel >
bool CGAL::read_xyz_points_and_normals (std::istream &stream, OutputIterator output, PointPMap point_pmap, NormalPMap normal_pmap, const Kernel &)
 Reads points (positions + normals, if available) from a .xyz ASCII stream. More...
 
template<typename OutputIteratorValueType , typename OutputIterator , typename PointPMap , typename Kernel >
bool CGAL::read_xyz_points (std::istream &stream, OutputIterator output, PointPMap point_pmap, const Kernel &kernel)
 Reads points (positions only) from a .xyz ASCII stream. More...
 
template<typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
bool CGAL::write_off_points_and_normals (std::ostream &stream, ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, const Kernel &)
 Saves the [first, beyond) range of points (positions + normals) to a .off ASCII stream. More...
 
template<typename ForwardIterator , typename PointPMap , typename Kernel >
bool CGAL::write_off_points (std::ostream &stream, ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, const Kernel &)
 Saves the [first, beyond) range of points (positions only) to a .off ASCII stream. More...
 
template<typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
bool CGAL::write_xyz_points_and_normals (std::ostream &stream, ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, const Kernel &)
 Saves the [first, beyond) range of points (positions + normals) to a .xyz ASCII stream. More...
 
template<typename ForwardIterator , typename PointPMap , typename Kernel >
bool CGAL::write_xyz_points (std::ostream &stream, ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, const Kernel &)
 Saves the [first, beyond) range of points (positions only) to a .xyz ASCII stream. More...
 
template<typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel , typename SvdTraits >
void CGAL::jet_estimate_normals (ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, unsigned int k, const Kernel &, unsigned int degree_fitting=2)
 Estimates normal directions of the [first, beyond) range of points using jet fitting on the k nearest neighbors. More...
 
template<typename InputIterator , typename PointPMap , typename Kernel , typename SvdTraits >
void CGAL::jet_smooth_point_set (InputIterator first, InputIterator beyond, PointPMap point_pmap, unsigned int k, const Kernel &, unsigned int degree_fitting=2, unsigned int degree_monge=2)
 Smoothes the [first, beyond) range of points using jet fitting on the k nearest neighbors and reprojection onto the jet. More...
 
template<typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
ForwardIterator CGAL::mst_orient_normals (ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, unsigned int k, const Kernel &kernel)
 Orients the normals of the [first, beyond) range of points using the propagation of a seed orientation through a minimum spanning tree of the Riemannian graph [Hoppe92]. More...
 
template<typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
void CGAL::pca_estimate_normals (ForwardIterator first, ForwardIterator beyond, PointPMap point_pmap, NormalPMap normal_pmap, unsigned int k, const Kernel &)
 Estimates normal directions of the [first, beyond) range of points by linear least squares fitting of a plane over the k nearest neighbors. More...
 
template<typename ForwardIterator , typename PointPMap , typename Kernel >
ForwardIterator CGAL::random_simplify_point_set (ForwardIterator first, ForwardIterator beyond, PointPMap, double removed_percentage, const Kernel &)
 Randomly deletes a user-specified fraction of the input points. More...
 
template<typename InputIterator , typename PointPMap , typename Kernel >
InputIterator CGAL::remove_outliers (InputIterator first, InputIterator beyond, PointPMap point_pmap, unsigned int k, double threshold_percent, const Kernel &)
 Removes outliers: More...
 
template<typename Concurrency_tag , typename OutputIterator , typename RandomAccessIterator , typename PointPMap , typename Kernel >
OutputIterator CGAL::wlop_simplify_and_regularize_point_set (RandomAccessIterator first, RandomAccessIterator beyond, OutputIterator output, PointPMap point_pmap, double select_percentage, double radius, unsigned int iter_number, bool require_uniform_sampling, const Kernel &)
 This is an implementation of the Weighted Locally Optimal Projection (WLOP) simplification algorithm. More...
 

Function Documentation

template<typename Concurrency_tag , typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
double CGAL::bilateral_smooth_point_set ( ForwardIterator  first,
ForwardIterator  beyond,
PointPMap  point_pmap,
NormalPMap  normal_pmap,
unsigned int  k,
typename Kernel::FT  sharpness_angle,
const Kernel  
)

This function smooths an input point set by iteratively projecting each point onto the implicit surface patch fitted over its k nearest neighbors.

Bilateral projection preserves sharp features according to the normal (gradient) information. Both point positions and normals will be modified. For more details, please see section 4 in [3].

A parallel version of this function is provided and requires the executable to be linked against the Intel TBB library. To control the number of threads used, the user may use the tbb::task_scheduler_init class. See the TBB documentation for more details.

Precondition
Normals must be unit vectors
k >= 2
Template Parameters
Concurrency_tagenables sequential versus parallel algorithm. Possible values are Sequential_tag and Parallel_tag.
ForwardIteratoriterator over input points.
PointPMapis a model of ReadWritePropertyMap with the value type of ForwardIterator as key and Kernel::Point_3 as value type. It can be omitted if the value type of ForwardIterator is convertible to Kernel::Point_3.
NormalPMapis a model of ReadWritePropertyMap with the value type of ForwardIterator as key and Kernel::Vector_3 as value type.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap using Kernel_traits.
Returns
Average point movement error. It's a convergence criterium for the algorithm. This value can help the user to decide how many iterations are sufficient.
Parameters
firstforward iterator on the first input point.
beyondpast-the-end iterator.
point_pmappoint property map.
normal_pmapnormal property map.
ksize of the neighborhood for the implicit surface patch fitting. The larger the value is, the smoother the result will be.
sharpness_anglecontrols the sharpness of the result. The larger the value is, the smoother the result will be. The range of possible value is [0, 90].

#include <CGAL/bilateral_smooth_point_set.h>

template<typename InputIterator , typename PointPMap , typename Kernel >
Kernel::FT CGAL::compute_average_spacing ( InputIterator  first,
InputIterator  beyond,
PointPMap  point_pmap,
unsigned int  k,
const Kernel  
)

Computes average spacing from k nearest neighbors.

Precondition
k >= 2.
Template Parameters
InputIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of InputIterator is convertible to Point_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
average spacing (scalar).
Parameters
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of InputIterator -> Point_3
knumber of neighbors.

#include <CGAL/compute_average_spacing.h>

Examples:
Point_set_processing_3/average_spacing_example.cpp.
template<typename OutputIterator , typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
OutputIterator CGAL::edge_aware_upsample_point_set ( ForwardIterator  first,
ForwardIterator  beyond,
OutputIterator  output,
PointPMap  point_pmap,
NormalPMap  normal_pmap,
const typename Kernel::FT  sharpness_angle,
typename Kernel::FT  edge_sensitivity,
typename Kernel::FT  neighbor_radius,
const unsigned int  number_of_output_points,
const Kernel  
)

This method progressively upsamples the point set while approaching the edge singularities (detected by normal variation), which generates a denser point set from an input point set.

This has applications in point-based rendering, hole filling, and sparse surface reconstruction. Normals of points are required as input. For more details, please refer to [3].

Template Parameters
OutputIteratorType of the output iterator. The type of the objects put in it is std::pair<Kernel::Point_3, Kernel::Vector_3>. Note that the user may use a function_output_iterator to match specific needs.
ForwardIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with the value type of ForwardIterator as key and Kernel::Point_3 as value type. It can be omitted if the value type of ForwardIterator is convertible to Kernel::Point_3.
NormalPMapis a model of ReadablePropertyMap with the value type of ForwardIterator as key and Kernel::Vector_3 as value type.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap using Kernel_traits.
Parameters
firstforward iterator on the first input point.
beyondpast-the-end iterator.
outputoutput iterator where output points and normals are put.
point_pmappoint property map.
normal_pmapvector property map.
sharpness_anglecontrols the preservation of sharp features. The larger the value is, the smoother the result will be. The range of possible value is [0, 90]. See section Parameter: sharpness_angle for an example.
edge_sensitivitylarger values of edge-sensitivity give higher priority to inserting points along sharp features. The range of possible values is [0, 1]. See section Parameter: edge_sensitivity for an example.
neighbor_radiusindicates the radius of the largest hole that should be filled. The default value is set to 3 times the average spacing of the point set. If the value given by user is smaller than the average spacing, the function will use the default value instead.
number_of_output_pointsnumber of output points to generate.

#include <CGAL/edge_aware_upsample_point_set.h>

Examples:
Point_set_processing_3/edge_aware_upsample_point_set_example.cpp.
template<typename ForwardIterator , typename PointPMap , typename Kernel >
ForwardIterator CGAL::grid_simplify_point_set ( ForwardIterator  first,
ForwardIterator  beyond,
PointPMap  point_pmap,
double  epsilon,
const Kernel  
)

Merges points which belong to the same cell of a grid of cell size = epsilon.

This method modifies the order of input points so as to pack all remaining points first, and returns an iterator over the first point to remove (see erase-remove idiom). For this reason it should not be called on sorted containers.

Precondition
epsilon > 0
Template Parameters
ForwardIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of ForwardIterator is convertible to Point_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
iterator over the first point to remove.
Parameters
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of ForwardIterator -> Point_3
epsilontolerance value when merging 3D points.

#include <CGAL/grid_simplify_point_set.h>

Examples:
Point_set_processing_3/grid_simplification_example.cpp.
template<typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel , typename SvdTraits >
void CGAL::jet_estimate_normals ( ForwardIterator  first,
ForwardIterator  beyond,
PointPMap  point_pmap,
NormalPMap  normal_pmap,
unsigned int  k,
const Kernel ,
unsigned int  degree_fitting = 2 
)

Estimates normal directions of the [first, beyond) range of points using jet fitting on the k nearest neighbors.

The output normals are randomly oriented.

Precondition
k >= 2
Template Parameters
ForwardIteratoriterator model of the concept of the same name over input points and able to store output normals.
PointPMapis a model of ReadablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of ForwardIterator is convertible to Point_3<Kernel>.
NormalPMapis a model of WritablePropertyMap with value type Vector_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
SvdTraitstemplate parameter for the class Monge_via_jet_fitting that can be ommited under conditions described in the documentation of Monge_via_jet_fitting.
Parameters
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of ForwardIterator -> Point_3.
normal_pmapproperty map: value_type of ForwardIterator -> Vector_3.
knumber of neighbors.
degree_fittingfitting degree

#include <CGAL/jet_estimate_normals.h>

template<typename InputIterator , typename PointPMap , typename Kernel , typename SvdTraits >
void CGAL::jet_smooth_point_set ( InputIterator  first,
InputIterator  beyond,
PointPMap  point_pmap,
unsigned int  k,
const Kernel ,
unsigned int  degree_fitting = 2,
unsigned int  degree_monge = 2 
)

Smoothes the [first, beyond) range of points using jet fitting on the k nearest neighbors and reprojection onto the jet.

As this method relocates the points, it should not be called on containers sorted w.r.t. point locations.

Precondition
k >= 2
Template Parameters
InputIteratoriterator over input points.
PointPMapis a model of ReadWritePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of InputIterator is convertible to Point_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
SvdTraitstemplate parameter for the class Monge_via_jet_fitting that can be ommited under conditions described in the documentation of Monge_via_jet_fitting.
Parameters
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of InputIterator -> Point_3.
knumber of neighbors.
degree_fittingfitting degree
degree_mongeMonge degree

#include <CGAL/jet_smooth_point_set.h>

Examples:
Point_set_processing_3/jet_smoothing_example.cpp.
template<typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
ForwardIterator CGAL::mst_orient_normals ( ForwardIterator  first,
ForwardIterator  beyond,
PointPMap  point_pmap,
NormalPMap  normal_pmap,
unsigned int  k,
const Kernel kernel 
)

Orients the normals of the [first, beyond) range of points using the propagation of a seed orientation through a minimum spanning tree of the Riemannian graph [Hoppe92].

This method modifies the order of input points so as to pack all sucessfully oriented points first, and returns an iterator over the first point with an unoriented normal (see erase-remove idiom). For this reason it should not be called on sorted containers.

Warning
This function may fail when Boost version 1.54 is used, because of the following bug: https://svn.boost.org/trac/boost/ticket/9012
Precondition
Normals must be unit vectors
k >= 2
Template Parameters
ForwardIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of ForwardIterator is convertible to Point_3<Kernel>.
NormalPMapis a model of ReadWritePropertyMap with value type Vector_3<Kernel> .
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
iterator over the first point with an unoriented normal.
Parameters
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of ForwardIterator -> Point_3.
normal_pmapproperty map: value_type of ForwardIterator -> Vector_3.
knumber of neighbors
kernelgeometric traits.

#include <CGAL/mst_orient_normals.h>

Examples:
Point_set_processing_3/normals_example.cpp.
template<typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
void CGAL::pca_estimate_normals ( ForwardIterator  first,
ForwardIterator  beyond,
PointPMap  point_pmap,
NormalPMap  normal_pmap,
unsigned int  k,
const Kernel  
)

Estimates normal directions of the [first, beyond) range of points by linear least squares fitting of a plane over the k nearest neighbors.

The output normals are randomly oriented.

Precondition
k >= 2
Template Parameters
ForwardIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of ForwardIterator is convertible to Point_3<Kernel>.
NormalPMapis a model of WritablePropertyMap with value type Vector_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Parameters
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of ForwardIterator -> Point_3.
normal_pmapproperty map: value_type of ForwardIterator -> Vector_3.
knumber of neighbors.

#include <CGAL/pca_estimate_normals.h>

Examples:
Point_set_processing_3/normals_example.cpp.
template<typename ForwardIterator , typename PointPMap , typename Kernel >
ForwardIterator CGAL::random_simplify_point_set ( ForwardIterator  first,
ForwardIterator  beyond,
PointPMap  ,
double  removed_percentage,
const Kernel  
)

Randomly deletes a user-specified fraction of the input points.

This method modifies the order of input points so as to pack all remaining points first, and returns an iterator over the first point to remove (see erase-remove idiom). For this reason it should not be called on sorted containers.

Template Parameters
ForwardIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of ForwardIterator is convertible to Point_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
iterator over the first point to remove.
Parameters
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
removed_percentagepercentage of points to remove.

#include <CGAL/random_simplify_point_set.h>

template<typename OutputIteratorValueType , typename OutputIterator , typename PointPMap , typename Kernel >
bool CGAL::read_off_points ( std::istream &  stream,
OutputIterator  output,
PointPMap  point_pmap,
const Kernel kernel 
)

Reads points (position only) from a .off ASCII stream.

The function expects for each point a line with the x y z position. If the position is followed by the nx ny nz normal, then the normal will be ignored. Faces are ignored.

Template Parameters
OutputIteratorValueTypetype of objects that can be put in OutputIterator. It is default to value_type_traits<OutputIterator>::type and can be omitted when the default is fine.
OutputIteratoriterator over output points.
PointPMapis a model of WritablePropertyMap with value_type Point_3<Kernel>. It can be omitted if the value type of OutputIterator is convertible to Point_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
true on success.
Parameters
streaminput stream.
outputoutput iterator over points.
point_pmapproperty map: value_type of OutputIterator -> Point_3.
kernelgeometric traits.

#include <CGAL/IO/read_off_points.h>

template<typename OutputIteratorValueType , typename OutputIterator , typename PointPMap , typename NormalPMap , typename Kernel >
bool CGAL::read_off_points_and_normals ( std::istream &  stream,
OutputIterator  output,
PointPMap  point_pmap,
NormalPMap  normal_pmap,
const Kernel  
)

Reads points (positions + normals, if available) from a .off ASCII stream.

The function expects for each point a line with the x y z position, optionally followed by the nx ny nz normal. Faces are ignored.

Template Parameters
OutputIteratorValueTypetype of objects that can be put in OutputIterator. It is default to value_type_traits<OutputIterator>::type and can be omitted when the default is fine.
OutputIteratoriterator over output points.
PointPMapis a model of WritablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of OutputIterator is convertible to Point_3<Kernel>.
NormalPMapis a model of WritablePropertyMap with value type Vector_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
true on success.
Parameters
streaminput stream.
outputoutput iterator over points.
point_pmapproperty map: value_type of OutputIterator -> Point_3.
normal_pmapproperty map: value_type of OutputIterator -> Vector_3.

#include <CGAL/IO/read_off_points.h>

template<typename OutputIteratorValueType , typename OutputIterator , typename PointPMap , typename Kernel >
bool CGAL::read_xyz_points ( std::istream &  stream,
OutputIterator  output,
PointPMap  point_pmap,
const Kernel kernel 
)

Reads points (positions only) from a .xyz ASCII stream.

The function expects for each point a line with the x y z position. If the position is followed by the nx ny nz normal, then the normal will be ignored. The first line may contain the number of points in the file. Empty lines and comments starting by # character are allowed.

Template Parameters
OutputIteratorValueTypetype of objects that can be put in OutputIterator. It is default to value_type_traits<OutputIterator>::type and can be omitted when the default is fine.
OutputIteratoriterator over output points.
PointPMapis a model of WritablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of OutputIterator is convertible to Point_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
true on success.
Parameters
streaminput stream.
outputoutput iterator over points.
point_pmapproperty map: value_type of OutputIterator -> Point_3.
kernelgeometric traits.

#include <CGAL/IO/read_xyz_points.h>

Examples:
Point_set_processing_3/average_spacing_example.cpp, Point_set_processing_3/grid_simplification_example.cpp, Point_set_processing_3/normals_example.cpp, Point_set_processing_3/remove_outliers_example.cpp, and Point_set_processing_3/wlop_simplify_and_regularize_point_set_example.cpp.
template<typename OutputIteratorValueType , typename OutputIterator , typename PointPMap , typename NormalPMap , typename Kernel >
bool CGAL::read_xyz_points_and_normals ( std::istream &  stream,
OutputIterator  output,
PointPMap  point_pmap,
NormalPMap  normal_pmap,
const Kernel  
)

Reads points (positions + normals, if available) from a .xyz ASCII stream.

The function expects for each point a line with the x y z position, optionally followed by the nx ny nz normal. The first line may contain the number of points in the file. Empty lines and comments starting by # character are allowed.

Template Parameters
OutputIteratorValueTypetype of objects that can be put in OutputIterator. It is default to value_type_traits<OutputIterator>::type and can be omitted when the default is fine.
OutputIteratoriterator over output points.
PointPMapis a model of WritablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of OutputIterator value_type is convertible to Point_3<Kernel>.
NormalPMapis a model of WritablePropertyMap with value type Vector_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
true on success.
Parameters
streaminput stream.
outputoutput iterator over points.
point_pmapproperty map: value_type of OutputIterator -> Point_3.
normal_pmapproperty map: value_type of OutputIterator -> Vector_3.

#include <CGAL/IO/read_xyz_points.h>

Examples:
Point_set_processing_3/bilateral_smooth_point_set_example.cpp, Point_set_processing_3/edge_aware_upsample_point_set_example.cpp, and Point_set_processing_3/read_write_xyz_point_set_example.cpp.
template<typename InputIterator , typename PointPMap , typename Kernel >
InputIterator CGAL::remove_outliers ( InputIterator  first,
InputIterator  beyond,
PointPMap  point_pmap,
unsigned int  k,
double  threshold_percent,
const Kernel  
)

Removes outliers:

  • computes average squared distance to the K nearest neighbors,
  • and sorts the points in increasing order of average distance.

This method modifies the order of input points so as to pack all remaining points first, and returns an iterator over the first point to remove (see erase-remove idiom). For this reason it should not be called on sorted containers.

Precondition
k >= 2
Template Parameters
InputIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with value type Point_3<Kernel>. It can be omitted ifthe value type of InputIterator is convertible to Point_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
iterator over the first point to remove.
Parameters
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of InputIterator -> Point_3
knumber of neighbors.
threshold_percentpercentage of points to remove.

#include <CGAL/remove_outliers.h>

Examples:
Point_set_processing_3/remove_outliers_example.cpp.
template<typename Concurrency_tag , typename OutputIterator , typename RandomAccessIterator , typename PointPMap , typename Kernel >
OutputIterator CGAL::wlop_simplify_and_regularize_point_set ( RandomAccessIterator  first,
RandomAccessIterator  beyond,
OutputIterator  output,
PointPMap  point_pmap,
double  select_percentage,
double  radius,
unsigned int  iter_number,
bool  require_uniform_sampling,
const Kernel  
)

This is an implementation of the Weighted Locally Optimal Projection (WLOP) simplification algorithm.

The WLOP simplification algorithm can produce a set of denoised, outlier-free and evenly distributed particles over the original dense point cloud. The core of the algorithm is a Weighted Locally Optimal Projection operator with a density uniformization term. For more details, please refer to [2].

A parallel version of WLOP is provided and requires the executable to be linked against the Intel TBB library. To control the number of threads used, the user may use the tbb::task_scheduler_init class. See the TBB documentation for more details.

Template Parameters
Concurrency_tagenables sequential versus parallel algorithm. Possible values are Sequential_tag and Parallel_tag.
OutputIteratorType of the output iterator. It must accept objects of type Kernel::Point_3.
RandomAccessIteratorIterator over input points.
PointPMapis a model of ReadablePropertyMap with the value type of ForwardIterator as key type and Kernel::Point_3 as value type. It can be omitted if the value type of RandomAccessIterator is convertible to Kernel::Point_3.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap using Kernel_traits.
Parameters
firstrandom-access iterator to the first input point.
beyondpast-the-end iterator.
outputoutput iterator where output points are put.
point_pmappoint property map.
select_percentagepercentage of points to retain. The default value is set to 5 (%).
radiusspherical neighborhood radius. This is a key parameter that needs to be finely tuned. The result will be irregular if too small, but a larger value will impact the runtime. In practice, choosing a radius such that the neighborhood of each sample point includes at least two rings of neighboring sample points gives satisfactory result. The default value is set to 8 times the average spacing of the point set.
iter_numbernumber of iterations to solve the optimsation problem. The default value is 35. More iterations give a more regular result but increase the runtime.
require_uniform_samplingan optional preprocessing, which will give better result if the distribution of the input points is highly non-uniform. The default value is false.

#include <CGAL/wlop_simplify_and_regularize_point_set.h>

Examples:
Point_set_processing_3/wlop_simplify_and_regularize_point_set_example.cpp.
template<typename ForwardIterator , typename PointPMap , typename Kernel >
bool CGAL::write_off_points ( std::ostream &  stream,
ForwardIterator  first,
ForwardIterator  beyond,
PointPMap  point_pmap,
const Kernel  
)

Saves the [first, beyond) range of points (positions only) to a .off ASCII stream.

The function writes for each point a line with the x y z position.

Template Parameters
ForwardIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with a value_type = Point_3<Kernel>. It can be omitted if the value type of ForwardIterator is convertible to Point_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
true on success.
Parameters
streamoutput stream.
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of ForwardIterator -> Point_3.

#include <CGAL/IO/write_off_points.h>

template<typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
bool CGAL::write_off_points_and_normals ( std::ostream &  stream,
ForwardIterator  first,
ForwardIterator  beyond,
PointPMap  point_pmap,
NormalPMap  normal_pmap,
const Kernel  
)

Saves the [first, beyond) range of points (positions + normals) to a .off ASCII stream.

The function writes for each point a line with the x y z position followed by the nx ny nz normal.

Precondition
normals must be unit vectors
Template Parameters
ForwardIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of ForwardIterator is convertible to Point_3<Kernel>.
NormalPMapis a model of ReadablePropertyMap with a value type Vector_3<Kernel>.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
true on success.
Parameters
streamoutput stream.
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of ForwardIterator -> Point_3.
normal_pmapproperty map: value_type of ForwardIterator -> Vector_3.

#include <CGAL/IO/write_off_points.h>

template<typename ForwardIterator , typename PointPMap , typename Kernel >
bool CGAL::write_xyz_points ( std::ostream &  stream,
ForwardIterator  first,
ForwardIterator  beyond,
PointPMap  point_pmap,
const Kernel  
)

Saves the [first, beyond) range of points (positions only) to a .xyz ASCII stream.

The function writes for each point a line with the x y z position.

Template Parameters
ForwardIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with value type Point_3<Kernel>. It can be omitted if the value type of ForwardIterator value_type is convertible toPoint_3<Kernel>`.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
true on success.
Parameters
streamoutput stream.
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of ForwardIterator -> Point_3.

#include <CGAL/IO/write_xyz_points.h>

Examples:
Point_set_processing_3/wlop_simplify_and_regularize_point_set_example.cpp.
template<typename ForwardIterator , typename PointPMap , typename NormalPMap , typename Kernel >
bool CGAL::write_xyz_points_and_normals ( std::ostream &  stream,
ForwardIterator  first,
ForwardIterator  beyond,
PointPMap  point_pmap,
NormalPMap  normal_pmap,
const Kernel  
)

Saves the [first, beyond) range of points (positions + normals) to a .xyz ASCII stream.

The function writes for each point a line with the x y z position followed by the nx ny nz normal.

Precondition
normals must be unit vectors
Template Parameters
ForwardIteratoriterator over input points.
PointPMapis a model of ReadablePropertyMap with a value type = Point_3<Kernel>. It can be omitted if the value type of ForwardIterator value_type is convertible toPoint_3<Kernel>. @tparam NormalPMap is a model ofReadablePropertyMapwith a value typeVector_3<Kernel>`.
KernelGeometric traits class. It can be omitted and deduced automatically from the value type of PointPMap.
Returns
true on success.
Parameters
streamoutput stream.
firstiterator over the first input point.
beyondpast-the-end iterator over the input points.
point_pmapproperty map: value_type of ForwardIterator -> Point_3.
normal_pmapproperty map: value_type of ForwardIterator -> Vector_3.

#include <CGAL/IO/write_xyz_points.h>

Examples:
Point_set_processing_3/bilateral_smooth_point_set_example.cpp, Point_set_processing_3/edge_aware_upsample_point_set_example.cpp, and Point_set_processing_3/read_write_xyz_point_set_example.cpp.