Point Cloud Library (PCL)
1.7.0
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00001 /** 00002 \addtogroup kdtree Module kdtree 00003 00004 \section secKDtreePresentation Overview 00005 00006 The <b>pcl_kdtree</b> library provides the kd-tree data-structure, using 00007 <a href="http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN">FLANN</a>, 00008 that allows for fast <a href="http://en.wikipedia.org/wiki/Nearest_neighbor_search">nearest neighbor searches</a>. 00009 00010 A <a href="http://en.wikipedia.org/wiki/Kd-tree">Kd-tree</a> (<i>k</i>-dimensional tree) is a space-partitioning data 00011 structure that stores a set of k-dimensional points in a tree structure that enables efficient range searches and 00012 nearest neighbor searches. Nearest neighbor searches are a core operation when working with point cloud data and can 00013 be used to find correspondences between groups of points or feature descriptors or to define the local neighborhood 00014 around a point or points. 00015 00016 \image html http://www.pointclouds.org/assets/images/contents/documentation/kdtree_mug.png 00017 00018 \section secKDtreeRequirements Requirements 00019 - \ref common "common" 00020 00021 */