|
| template<typename ConcurrencyTag, typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| double | bilateral_smooth_point_set (PointRange &points, unsigned int k, const NamedParameters &np=parameters::default_values()) |
| | This function smooths an input point set by iteratively projecting each point onto the implicit surface patch fitted over its nearest neighbors.
|
| template<typename PointRange, typename ClusterMap, typename NamedParameters = parameters::Default_named_parameters> |
| std::size_t | cluster_point_set (PointRange &points, ClusterMap cluster_map, const NamedParameters &np=parameters::default_values()) |
| | Identifies connected components on a nearest neighbor graph built using a query sphere of fixed radius centered on each point.
|
| template<typename ConcurrencyTag, typename PointRange, typename NamedParameters = CGAL::parameters::Default_named_parameters> |
| FT | compute_average_spacing (const PointRange &points, unsigned int k, const NamedParameters &np=parameters::default_values()) |
| | Computes average spacing from k nearest neighbors.
|
| template<typename ConcurrencyTag, typename PointRange, typename OutputIterator, typename NamedParameters = parameters::Default_named_parameters> |
| OutputIterator | edge_aware_upsample_point_set (const PointRange &points, OutputIterator output, const NamedParameters &np=parameters::default_values()) |
| | 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.
|
| template<typename PointRange, typename QueryPointRange, typename OutputIterator, typename NamedParameters = parameters::Default_named_parameters> |
| OutputIterator | estimate_local_k_neighbor_scales (const PointRange &points, const QueryPointRange &queries, OutputIterator output, const NamedParameters &np=parameters::default_values()) |
| | Estimates the local scale in a K nearest neighbors sense on a set of user-defined query points.
|
| template<typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| std::size_t | estimate_global_k_neighbor_scale (const PointRange &points, const NamedParameters &np=parameters::default_values()) |
| | Estimates the global scale in a K nearest neighbors sense.
|
| template<typename PointRange, typename QueryPointRange, typename OutputIterator, typename NamedParameters = parameters::Default_named_parameters> |
| OutputIterator | estimate_local_range_scales (const PointRange &points, const QueryPointRange &queries, OutputIterator output, const NamedParameters &np=parameters::default_values()) |
| | Estimates the local scale in a range sense on a set of user-defined query points.
|
| template<typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| FT | estimate_global_range_scale (const PointRange &points, const NamedParameters &np=parameters::default_values()) |
| | Estimates the global scale in a range sense.
|
| template<typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| PointRange::iterator | grid_simplify_point_set (PointRange &points, double epsilon, const NamedParameters &np=parameters::default_values()) |
| | Merges points which belong to the same cell of a grid of cell size = epsilon.
|
| template<typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| PointRange::iterator | hierarchy_simplify_point_set (PointRange &points, const NamedParameters &np=parameters::default_values()) |
| | Recursively split the point set in smaller clusters until the clusters have fewer than size elements and until their variation factor is below var_max.
|
|
template<typename OutputIteratorValueType, typename OutputIterator, typename ... PropertyHandler> |
| bool | read_las_points_with_properties (std::istream &is, OutputIterator output, PropertyHandler &&... properties) |
|
template<typename OutputIteratorValueType, typename OutputIterator, typename NamedParameters = CGAL::parameters::Default_named_parameters> |
| bool | read_las_points (std::istream &is, OutputIterator output, const NamedParameters &np=parameters::default_values()) |
|
template<typename OutputIteratorValueType, typename OutputIterator, typename NamedParameters = CGAL::parameters::Default_named_parameters> |
| bool | read_off_points (std::istream &is, OutputIterator output, const NamedParameters &np=parameters::default_values()) |
|
template<typename OutputIteratorValueType, typename OutputIterator, typename ... PropertyHandler> |
| bool | read_ply_points_with_properties (std::istream &is, OutputIterator output, PropertyHandler &&... properties) |
|
template<typename OutputIteratorValueType, typename OutputIterator, typename NamedParameters = CGAL::parameters::Default_named_parameters> |
| bool | read_ply_points (std::istream &is, OutputIterator output, const NamedParameters &np=parameters::default_values()) |
|
template<typename OutputIteratorValueType, typename OutputIterator, typename NamedParameters = CGAL::parameters::Default_named_parameters> |
| bool | read_xyz_points (std::istream &is, OutputIterator output, const NamedParameters &np=parameters::default_values()) |
|
template<typename PointRange, typename PointMap, typename ... PropertyHandler> |
| bool | write_las_points_with_properties (std::ostream &os, const PointRange &points, std::tuple< PointMap, IO::LAS_property::X, IO::LAS_property::Y, IO::LAS_property::Z > point_property, PropertyHandler &&... properties) |
|
template<typename PointRange, typename NamedParameters = CGAL::parameters::Default_named_parameters> |
| bool | write_las_points (std::ostream &os, const PointRange &points, const NamedParameters &np=parameters::default_values()) |
|
template<typename PointRange, typename NamedParameters = CGAL::parameters::Default_named_parameters> |
| bool | write_off_points (std::ostream &os, const PointRange &points, const NamedParameters &np=parameters::default_values()) |
| template<typename PointRange, typename ... PropertyHandler> |
| bool | write_ply_points_with_properties (std::ostream &os, const PointRange &points, PropertyHandler &&... properties) |
|
template<typename PointRange, typename NamedParameters = CGAL::parameters::Default_named_parameters> |
| bool | write_ply_points (std::ostream &os, const PointRange &points, const NamedParameters &np=parameters::default_values()) |
|
template<typename PointRange, typename NamedParameters = CGAL::parameters::Default_named_parameters> |
| bool | write_xyz_points (std::ostream &os, const PointRange &points, const NamedParameters &np=parameters::default_values()) |
| template<typename ConcurrencyTag, typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| void | jet_estimate_normals (PointRange &points, unsigned int k, const NamedParameters &np=parameters::default_values()) |
| | Estimates normal directions of the range of points using jet fitting on the nearest neighbors.
|
| template<typename ConcurrencyTag, typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| void | jet_smooth_point_set (PointRange &points, unsigned int k, const NamedParameters &np=parameters::default_values()) |
| | Smoothes the range of points using jet fitting on the nearest neighbors and reprojection onto the jet.
|
| template<typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| PointRange::iterator | mst_orient_normals (PointRange &points, unsigned int k, const NamedParameters &np=parameters::default_values()) |
| | Orients the normals of the range of points using the propagation of a seed orientation through a minimum spanning tree of the Riemannian graph.
|
| template<typename ConcurrencyTag, typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| void | pca_estimate_normals (PointRange &points, unsigned int k, const NamedParameters &np=parameters::default_values()) |
| | Estimates normal directions of the range of points by linear least squares fitting of a plane over the nearest neighbors.
|
| template<class PointRange, class OutputIterator, class NamedParameters = parameters::Default_named_parameters> |
| void | poisson_eliminate (const PointRange &points, std::size_t number_of_points, OutputIterator output, const NamedParameters &np=parameters::default_values()) |
| | performs Poisson disk elimination with a desired output size.
|
| template<typename PointRange> |
| PointRange::iterator | random_simplify_point_set (PointRange &points, double removed_percentage) |
| | Randomly deletes a user-specified fraction of the input points.
|
| template<typename ConcurrencyTag, typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| PointRange::iterator | remove_outliers (PointRange &points, unsigned int k, const NamedParameters &np=parameters::default_values()) |
| | Removes outliers:
|
| template<typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| void | scanline_orient_normals (PointRange &points, const NamedParameters &np=parameters::default_values()) |
| | orients the normals of the range of points by estimating a line of sight and checking its consistency with the current normal orientation.
|
| template<typename PointRange, typename PlaneRange, typename OutputIterator, typename NamedParameters> |
| OutputIterator | structure_point_set (const PointRange &points, const PlaneRange &planes, OutputIterator output, double epsilon, const NamedParameters &np) |
| | This is an implementation of the Point Set Structuring algorithm.
|
| template<class FT, class VCMTraits> |
| bool | vcm_is_on_feature_edge (std::array< FT, 6 > &cov, double threshold, VCMTraits) |
| | determines if a point is on a sharp feature edge from a point set for which the Voronoi covariance Measures have been computed.
|
|
template<class FT> |
| bool | vcm_is_on_feature_edge (std::array< FT, 6 > &cov, double threshold) |
| template<typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| void | compute_vcm (const PointRange &points, std::vector< std::array< double, 6 > > &ccov, double offset_radius, double convolution_radius, const NamedParameters &np=parameters::default_values()) |
| | computes the Voronoi Covariance Measure (VCM) of a point cloud, a construction that can be used for normal estimation and sharp feature detection.
|
| template<typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| void | vcm_estimate_normals (PointRange &points, double offset_radius, double convolution_radius, const NamedParameters &np=parameters::default_values()) |
| | Estimates normal directions of the range of points using the Voronoi Covariance Measure with a radius for the convolution.
|
| template<typename PointRange, typename NamedParameters = parameters::Default_named_parameters> |
| void | vcm_estimate_normals (PointRange &points, double offset_radius, unsigned int k, const NamedParameters &np=parameters::default_values()) |
| | Estimates normal directions of the range of points using the Voronoi Covariance Measure with a number of neighbors for the convolution.
|
| template<typename ConcurrencyTag, typename PointRange, typename OutputIterator, typename NamedParameters = parameters::Default_named_parameters> |
| OutputIterator | wlop_simplify_and_regularize_point_set (PointRange &points, OutputIterator output, const NamedParameters &np=parameters::default_values()) |
| | This is an implementation of the Weighted Locally Optimal Projection (WLOP) simplification algorithm.
|
| template<typename PointMap> |
| std::tuple< PointMap, LAS_property::X, LAS_property::Y, LAS_property::Z > | make_las_point_writer (PointMap point_map) |
| | generates a LAS property handler to write 3D points.
|
1.17.0