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    <p>I can see two good ways to do this.</p> <ol> <li><p>If the points you are looking for are in some ordered axially aligned grid, then you can access the ones that are in a certain radius immediately. The way to do this is to get the x, y, z point and convert it to its grid position along with the radius to define the min and max grid positions for x, y, and z. You can then access those variables immediately. </p></li> <li><p>If the points are not in a form that's not axially aligned and ordered into a grid then you need to put it inot a form that will be quick to search. I would suggest the <strong>kd</strong> tree. It takes a searching operation from being <code>O(n)</code> to <code>O(log(n)</code>. The way it does it is to split the point set in half along the mean and repeat untill you have a fast searchable tree:</p></li> </ol> <p><img src="https://i.stack.imgur.com/GGODZ.gif" alt="enter image description here"></p> <p>The PCL (point cloud Library) will do this for your as well!</p> <p>Here is a link:</p> <p><a href="http://pointclouds.org/" rel="nofollow noreferrer">http://pointclouds.org/</a></p> <p>And a tutorial on kd trees with pcl:</p> <p><a href="http://pointclouds.org/documentation/tutorials/kdtree_search.php#kdtree-search" rel="nofollow noreferrer">http://pointclouds.org/documentation/tutorials/kdtree_search.php#kdtree-search</a></p> <p>In fact it even shows you the code for a radius search from an entered point into a kd tree stored point cloud. Look at <em>neighbours in radius search</em> on the tutorial page i have provided.</p> <p>Good Luck!</p>
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