PointCloudSimplification Class Reference

PointCloudSimplification provides various point cloud simplification algorithms. More...

#include <easy3d/algo/point_cloud_simplification.h>

Static Public Member Functions
static float	average_space (PointCloud *cloud, KdTreeSearch *kdtree=nullptr, int k=6, bool accurate=false, int samples=10000)
	Query the average spacing of a point cloud. More...
static std::vector< PointCloud::Vertex >	grid_simplification (PointCloud *cloud, float cell_size)
	Simplification of a point cloud using a regular grid covering the bounding box of the points. Simplification is done by keeping a representative point (chosen arbitrarily) for each cell of the grid. This is non-uniform simplification since the representative point is chosen arbitrarily. More...
static std::vector< PointCloud::Vertex >	uniform_simplification (PointCloud *cloud, float epsilon, KdTreeSearch *kdtree=nullptr)
	Uniformly downsample a point cloud based on a distance criterion. This function can also be used for removing duplicate points of a point cloud. More...
static std::vector< PointCloud::Vertex >	uniform_simplification (PointCloud *cloud, unsigned int num)
	Uniformly downsample a point cloud given the expected point number. More...

Detailed Description

PointCloudSimplification provides various point cloud simplification algorithms.

Member Function Documentation

average_space()

float average_space ( PointCloud *  cloud, KdTreeSearch *  kdtree = nullptr, int  k = 6, bool  accurate = false, int  samples = 10000  )

static

Query the average spacing of a point cloud.

Parameters

cloud	The point cloud.
k	The number of nearest points used.
accurate	True to use every point to get an accurate calculation; false to obtain aa approximate measure, which uses only a subset (i.e., less than samples) of the points.
samples	Use less than this number of points for the calculation.
kdtree	A kdtree defined on this point cloud. If null, a new kdtree will be built and used.

Returns

The average space of the point cloud.

grid_simplification()

std::vector< PointCloud::Vertex > grid_simplification ( PointCloud *  cloud, float  cell_size  )

static

Simplification of a point cloud using a regular grid covering the bounding box of the points. Simplification is done by keeping a representative point (chosen arbitrarily) for each cell of the grid. This is non-uniform simplification since the representative point is chosen arbitrarily.

Parameters

cloud	The point cloud.
cell_size	The size of the cells of the grid.

Returns

The indices of points to be deleted.

uniform_simplification() [1/2]

std::vector< PointCloud::Vertex > uniform_simplification ( PointCloud *  cloud, float  epsilon, KdTreeSearch *  kdtree = nullptr  )

static

Uniformly downsample a point cloud based on a distance criterion. This function can also be used for removing duplicate points of a point cloud.

Parameters

cloud	The point cloud.
epsilon	The minimum allowed distance between points. Two points with a distance smaller than this value are considered identical. After simplification, the distance of any point pair is larger than this value.
kdtree	A kdtree defined on this point cloud. If null, a new kdtree will be built and used.

Returns

The indices of points to be deleted.

uniform_simplification() [2/2]

std::vector< PointCloud::Vertex > uniform_simplification ( PointCloud *  cloud, unsigned int  num  )

static

Uniformly downsample a point cloud given the expected point number.

Parameters

cloud	The point cloud.
num	The expected point number, which must be less than or equal to the original point number.

Returns

The indices of points to be deleted.

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

• /Users/lnan/Documents/Projects/Easy3D/easy3d/algo/point_cloud_simplification.h
• /Users/lnan/Documents/Projects/Easy3D/easy3d/algo/point_cloud_simplification.cpp