KdTreeSearch_ANN Class Reference

KdTree implementation based on ANN. More...

#include <easy3d/kdtree/kdtree_search_ann.h>

Inheritance diagram for KdTreeSearch_ANN:

Public Member Functions
	KdTreeSearch_ANN (const PointCloud *cloud)
	Constructor.
	KdTreeSearch_ANN (const std::vector< vec3 > &points)
	Constructor.
Closest point query
int	find_closest_point (const vec3 &p, float &squared_distance) const override
	Queries the closest point for a given point.
int	find_closest_point (const vec3 &p) const override
	Queries the closest point for a given point.
K nearest neighbors search
void	find_closest_k_points (const vec3 &p, int k, std::vector< int > &neighbors, std::vector< float > &squared_distances) const override
	Queries the K nearest neighbors for a given point.
void	find_closest_k_points (const vec3 &p, int k, std::vector< int > &neighbors) const override
	Queries the K nearest neighbors for a given point.
Fixed radius search
void	set_k_for_radius_search (int k)
	Specifies the K for fixed range search.
void	find_points_in_range (const vec3 &p, float squared_radius, std::vector< int > &neighbors, std::vector< float > &squared_distances) const override
	Queries the nearest neighbors within a fixed range.
void	find_points_in_range (const vec3 &p, float squared_radius, std::vector< int > &neighbors) const override
	Queries the nearest neighbors within a fixed range.
Public Member Functions inherited from KdTreeSearch
	KdTreeSearch (const PointCloud *cloud)
	Constructor.
	KdTreeSearch (const std::vector< vec3 > &points)
	Constructor.

Detailed Description

KdTree implementation based on ANN.

See also

KdTreeSearch_ETH, KdTreeSearch_FLANN, and KdTreeSearch_NanoFLANN.

Constructor & Destructor Documentation

KdTreeSearch_ANN() [1/2]

KdTreeSearch_ANN ( const PointCloud * cloud )

explicit

Constructor.

Parameters

cloud

The point cloud for which a KdTree will be constructed.

KdTreeSearch_ANN() [2/2]

KdTreeSearch_ANN ( const std::vector< vec3 > & points )

explicit

Constructor.

Parameters

points

The points for which a KdTree will be constructed.

Member Function Documentation

find_closest_k_points() [1/2]

void find_closest_k_points ( const vec3 & p, int k, std::vector< int > & neighbors ) const

overridevirtual

Queries the K nearest neighbors for a given point.

Parameters

p	The query point.
k	The number of required neighbors.
neighbors	The indices of the neighbors found.

Implements KdTreeSearch.

find_closest_k_points() [2/2]

void find_closest_k_points ( const vec3 & p, int k, std::vector< int > & neighbors, std::vector< float > & squared_distances ) const

overridevirtual

Queries the K nearest neighbors for a given point.

Parameters

p	The query point.
k	The number of required neighbors.
neighbors	The indices of the neighbors found.
squared_distances	The squared distances between the query point and its K nearest neighbors. The values are stored in accordance with their indices.

Note

The squared distances are returned by the argument squared_distances.

Implements KdTreeSearch.

find_closest_point() [1/2]

int find_closest_point ( const vec3 & p ) const

overridevirtual

Queries the closest point for a given point.

Parameters

p	The query point.

Returns

The index of the nearest neighbor found.

Implements KdTreeSearch.

find_closest_point() [2/2]

int find_closest_point ( const vec3 & p, float & squared_distance ) const

overridevirtual

Queries the closest point for a given point.

Parameters

p	The query point.
squared_distance	The squared distance between the query point and its closest neighbor.

Note

A squared distance is returned by the second argument squared_distance.

Returns

The index of the nearest neighbor found.

Implements KdTreeSearch.

find_points_in_range() [1/2]

void find_points_in_range ( const vec3 & p, float squared_radius, std::vector< int > & neighbors ) const

overridevirtual

Queries the nearest neighbors within a fixed range.

Parameters

p	The query point.
squared_radius	The search range (which is required to be squared).
neighbors	The indices of the neighbors found.

Implements KdTreeSearch.

find_points_in_range() [2/2]

void find_points_in_range ( const vec3 & p, float squared_radius, std::vector< int > & neighbors, std::vector< float > & squared_distances ) const

overridevirtual

Queries the nearest neighbors within a fixed range.

Parameters

p	The query point.
squared_radius	The search range (which is required to be squared).
neighbors	The indices of the neighbors found.
squared_distances	The squared distances between the query point and the neighbors found. The values are stored in accordance with their indices.

Note

The squared distances are returned by the argument squared_distances.

Implements KdTreeSearch.

set_k_for_radius_search()

void set_k_for_radius_search ( int k )

inline

Specifies the K for fixed range search.

ANN's annkFRSearch() needs to specify k. ANN's fixed range search is done in two steps. First, it computes the k nearest neighbors within the radius bound. Second, it returns the total number of points lying within the radius bound. It is permitted to set k = 0, in which case it only answers a range counting query.

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The documentation for this class was generated from the following files:

• G:/3_code/Easy3D/easy3d/kdtree/kdtree_search_ann.h
• G:/3_code/Easy3D/easy3d/kdtree/kdtree_search_ann.cpp