KdTree

https://pointclouds.org/documentation/classpcl_1_1search_1_1_kd_tree.html

search.KdTree is a wrapper class which inherits the pcl::KdTree class for performing search functions using KdTree structure.

Constructor

new PCL.SearchKdTree(pointType, sorted);

Parameters:

Name	Type	Default	Description
pointType	PointType	PointXYZ	The point cloud type.
sorted	boolean	true	Set to true if the application that the tree will be used for requires sorted nearest neighbor indices (default).

Methods

setSortedResults()

setSortedResults(sorted);

Parameters:

Name	Type	Default	Description
sorted	boolean		Set to true if the application that the tree will be used for requires sorted nearest neighbor indices.

setEpsilon()

setEpsilon(eps);

Set the search epsilon precision (error bound) for nearest neighbors searches.

Parameters:

Name	Type	Default	Description
eps	number		Precision (error bound) for nearest neighbors searches

nearestKSearch()

nearestKSearch(point, k);

Search for k-nearest neighbors for the given query point.

For Exmaple:

import * as PCL from 'pcl.js'

await PCL.init();

const point = new PCL.PointXYZ(1, 2, 3);
const k = 5
const kdtree = new PCL.SearchKdTree(pointType, sorted);
kdtree.nearestKSearch(point, k);

警告

This method does not do any bounds checking for the input index (i.e., index >= cloud.size () || index < 0), and assumes valid (i.e., finite) data.

Parameters:

Name	Type	Default	Description
point	PointType		A given valid (i.e., finite) query point
k	number		The number of neighbors to search for

Returns:

Name	Type
result	{ indices: Vector<number>; distances: Vector<number> }

radiusSearch()

radiusSearch(point, radius);

Search for all the nearest neighbors of the query point in a given radius.

警告

This method does not do any bounds checking for the input index (i.e., index >= cloud.size () || index < 0), and assumes valid (i.e., finite) data.

Parameters:

Name	Type	Default	Description
point	PointType		A given valid (i.e., finite) query point
radius	number		The radius of the sphere bounding all of p_q's neighbors

Returns:

Name	Type
result	{ indices: Vector<number>; distances: Vector<number> }

setInputCloud

See PassThrough.setInputCloud

getInputCloud

See PassThrough.getInputCloud