title: How does it work comparing/matching images with kd-trees and nearest neighbor search?
body: <p>I have been querying google for some material about kd-trees and image comparison but I couldn't make the 'link' between the technics for image comparison using kd-trees.
  Firstly, I found some articles talking about speed improvement with randomized kd-trees, then I was introduced to SIFT. After understanding basically how SIFT works, I read about nearest neighbor search. </p>
  
  <p>My real question is: If I have a mesh of points from SIFT, then I create the kd-tree for every image. How the nearest neighbor search can help me compare the images? At first, I thought that comparing images with a tree would work with some algorithm checking the tree structure and how near every point is from an image A from a point in the same node in and image B.</p>
  
  <p>If the question is too dumb, please suggest material or some topic for search.</p>
  
  <p>Thank you!</p>