CGAL 5.4.1 - Shape Detection
CGAL::Shape_detection::Shape_base< Traits > Class Template Referenceabstract

#include <CGAL/Shape_detection/Efficient_RANSAC/Shape_base.h>

Inherited by CGAL::Shape_detection::Cone< Traits >, CGAL::Shape_detection::Cylinder< Traits >, CGAL::Shape_detection::Plane< Traits >, CGAL::Shape_detection::Sphere< Traits >, and CGAL::Shape_detection::Torus< Traits >.

Definition

Base class for shape types that defines an interface to construct a shape from a set of points and to compute the point distance and normal deviation from the surface normal.

It is used during detection to identify the inliers from the input data and to extract the largest connected component in the inlier points.

Examples:
Shape_detection/include/efficient_RANSAC_with_custom_shape.h.

Public Types

typedef Traits::FT FT
 Number type.
 
typedef Traits::Point_3 Point_3
 Point type.
 
typedef Traits::Vector_3 Vector_3
 Vector type.
 

Public Member Functions

const std::vector< std::size_t > & indices_of_assigned_points () const
 Returns the indices of the points in the input range assigned to this shape.
 
virtual std::string info () const
 Returns a string containing the shape type and the numerical parameters.
 
virtual FT squared_distance (const Point_3 &p) const =0
 Computes the squared Euclidean distance from the query point p to the shape.
 

Protected Member Functions

virtual void create_shape (const std::vector< std::size_t > &indices)=0
 Constructs the shape based on a minimal set of samples from the input data.
 
virtual std::size_t connected_component (std::vector< std::size_t > &indices, FT cluster_epsilon)
 Determines the largest cluster of inlier points. More...
 
std::size_t connected_component_kdTree (std::vector< std::size_t > &indices, FT cluster_epsilon)
 Determines the largest cluster with a point-to-point distance not larger than cluster_epsilon. More...
 
virtual void squared_distance (const std::vector< std::size_t > &indices, std::vector< FT > &distances) const =0
 Computes the squared Euclidean distance from a set of points to the shape. More...
 
virtual void cos_to_normal (const std::vector< std::size_t > &indices, std::vector< FT > &angles) const =0
 Computes the deviation of the point normal from the surface normal at the projected point in form of the dot product and writes the result into the provided angles vector.
 
virtual std::size_t minimum_sample_size () const =0
 Returns minimal number of sample points required for construction.
 
boost::property_traits< typename Traits::Point_map >::reference point (std::size_t i) const
 Retrieves the point location from its index.
 
boost::property_traits< typename Traits::Normal_map >::reference normal (std::size_t i) const
 Retrieves the normal vector from its index.
 
const Traits & traits () const
 Retrieves the traits class.
 

Member Function Documentation

◆ connected_component()

template<class Traits >
virtual std::size_t CGAL::Shape_detection::Shape_base< Traits >::connected_component ( std::vector< std::size_t > &  indices,
FT  cluster_epsilon 
)
protectedvirtual

Determines the largest cluster of inlier points.

A point belongs to a cluster if there is a point in the cluster closer than cluster_epsilon distance.

◆ connected_component_kdTree()

template<class Traits >
std::size_t CGAL::Shape_detection::Shape_base< Traits >::connected_component_kdTree ( std::vector< std::size_t > &  indices,
FT  cluster_epsilon 
)
protected

Determines the largest cluster with a point-to-point distance not larger than cluster_epsilon.

This general version performs a region growing within the inliers using a Kd-tree.

◆ squared_distance()

template<class Traits >
virtual void CGAL::Shape_detection::Shape_base< Traits >::squared_distance ( const std::vector< std::size_t > &  indices,
std::vector< FT > &  distances 
) const
protectedpure virtual

Computes the squared Euclidean distance from a set of points to the shape.

The distances will be stored in the so called parameter.