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| 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.
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| 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.
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| 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.
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| 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.
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| 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.
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| 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.
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| 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.
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| 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.
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| 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.
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| 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.
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template<typename OutputIteratorValueType , typename OutputIterator , typename ... PropertyHandler> |
| bool | read_las_points_with_properties (std::istream &is, OutputIterator output, PropertyHandler &&... properties) |
| |
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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()) |
| |
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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()) |
| |
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template<typename OutputIteratorValueType , typename OutputIterator , typename ... PropertyHandler> |
| bool | read_ply_points_with_properties (std::istream &is, OutputIterator output, PropertyHandler &&... properties) |
| |
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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()) |
| |
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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()) |
| |
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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) |
| |
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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()) |
| |
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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()) |
| |
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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.
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| |
| 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.
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| 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.
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| |
| 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.
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| template<typename PointRange > |
| PointRange::iterator | random_simplify_point_set (PointRange &points, double removed_percentage) |
| | Randomly deletes a user-specified fraction of the input points.
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| |
| 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:
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| |
| 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.
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| |
| 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.
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| |
| 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.
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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.
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| |
| 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.
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| |
| 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.
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| |
| 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.
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1.9.6