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/**
\addtogroup kdtree Module kdtree
\section secKDtreePresentation Overview
The <b>pcl_kdtree</b> library provides the kd-tree data-structure, using
<a href="http://www.cs.ubc.ca/research/flann/</a>,
that allows for fast <a href="http://en.wikipedia.org/wiki/Nearest_neighbor_search">nearest neighbor searches</a>.
A <a href="http://en.wikipedia.org/wiki/Kd-tree">Kd-tree</a> (<i>k</i>-dimensional tree) is a space-partitioning data
structure that stores a set of k-dimensional points in a tree structure that enables efficient range searches and
nearest neighbor searches. Nearest neighbor searches are a core operation when working with point cloud data and can
be used to find correspondences between groups of points or feature descriptors or to define the local neighborhood
around a point or points.
\image html http://www.pointclouds.org/assets/images/contents/documentation/kdtree_mug.png
\section secKDtreeRequirements Requirements
- \ref common "common"
*/
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