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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"><html> <head> <meta http-equiv="content-type" content="text/html; charset=ISO-8859-1"> <title>Simple kd-Trees Source Code Documentation</title> </head> <body> <a name="top"></a> <table width=100%><tr> <td><a href="http://www.autonlab.org">www.autonlab.org</a></td> <td align=right><small>ver. 2004-06-18</small></td> </table> <hr> <table border=1 cellpadding=6 width=100% bgcolor="#bad1d"><td> <h3><center>Simple kd-Trees Source Code Documentation</center></h3> </table><p><!-- --------------------------------------------------------- --><a name="overview"></a><p><p>This package contains source code for the simkd kd-tree implementation. If you are not interested in the source code for this algorithm, please see the software link 'Simple kd-Trees' which contains binary versions of this algorithm with a nice user interface.</p><p>This program constructs a kd-tree from the contents of an input dataset of k-dimensional vectors, and then performs nearest neighbor searches within the kd-tree using query points from a query dataset. The search can be either for K nearest neighbors, or for all neighbors within some range (radius) of the query point. (Annoying note: the k's in kd-tree and k-nearest neighbor are not the same.) </p><table width=100% bgcolor="#bad1d"><td><h3>Documentation</h3></table><p>Source code readme: <a href="readme.txt">readme.txt</a><p>Documentation for the related <a href="../169">'Simple kd-Trees'</a> software:<a href="../169/simkd_applic_doc.html">simkd_applic_doc.html</a><p><!-- --------------------------------------------------------- --> </body></html>⌨️ 快捷键说明
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