<div class="gmail_quote">On Sat, Nov 28, 2009 at 11:42 AM, motes motes <span dir="ltr"><<a href="mailto:mort.motes@gmail.com">mort.motes@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
I am looking at itkOctreeTest.cxx which runs a test on an octree. The<br>
octree is build from a 3D image where each pixel has a value.<br>
<br>
My question is now. Is it possible to use the above octree as<br>
structure to find the k-nn to a point p?<br>
<br>
Assume that we have a 3D image which contains 12*12*12 nodes<br>
distributed randomly in the volume. Now for a given point p in the<br>
volume, the nodes within a specified radius r should be returned.<br>
<br>
As I understand the octree returns values of pixels and not locations<br>
but maybe with some modification it could be possible to convert this<br>
into locations? Does anyone have an idea for this?<br>
<br></blockquote><div><br>My understanding is that typical practice says to use a kdtree for NN searches and an octree for ray intersections (although I've found the modified-BSP tree to be MUCH faster at ray intersections). Can someone verify this?<br>
<br>Were you having a problem doing a NN search with the ITK kdtree?<br><br clear="all">Thanks,<br><br>David<br></div></div>