KdTreeSearch_FLANN Class Reference

KdTree implementation based on FLANN. More...

#include <easy3d/kdtree/kdtree_search_flann.h>

Inheritance diagram for KdTreeSearch_FLANN:

Public Member Functions
	KdTreeSearch_FLANN (const PointCloud *cloud)
	Constructor.
	KdTreeSearch_FLANN (const std::vector< vec3 > &points)
	Constructor.
void	set_checks (int chk)
	Specifies the maximum number of leaves to visit when searching for neighbors.
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	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 FLANN.

See also

KdTreeSearch_ANN, KdTreeSearch_ETH, and KdTreeSearch_NanoFLANN.

Constructor & Destructor Documentation

KdTreeSearch_FLANN() [1/2]

KdTreeSearch_FLANN ( const PointCloud * cloud )

explicit

Constructor.

Parameters

cloud

The point cloud for which a KdTree will be constructed.

KdTreeSearch_FLANN() [2/2]

KdTreeSearch_FLANN ( 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_checks()

void set_checks

(

int

chk

)

Specifies the maximum number of leaves to visit when searching for neighbors.

Parameters

chk

The maximum number of leaves to visit. A higher value for this parameter would give better search precision, but also take more time. For all leaves to be checked use the value FLANN_CHECKS_UNLIMITED. If automatic configuration was used when the index was created, the number of checks required to achieve the specified precision was also computed, to use that value specify FLANN_CHECKS_AUTOTUNED. The default value is FLANN_CHECKS_AUTOTUNED. (Liangliang: 32 is also a good value).

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

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