title: SIFT matches and recognition?
body: <p>I am developing an application where I am using SIFT + RANSAC and Homography to find an object (OpenCV C++,Java). The problem I am facing is that where there are many outliers RANSAC performs poorly.</p>
  
  <p>For this reasons I would like to try what the author of SIFT said to be pretty good: voting.</p>
  
  <p>I have read that we should vote in a 4 dimension feature space, where the 4 dimensions are:</p>
  
  <ul>
  <li>Location [x, y] (someone says Traslation)</li>
  <li>Scale</li>
  <li>Orientation</li>
  </ul>
  
  <p>While with opencv is easy to get the match <code>scale</code> and <code>orientation</code> with:</p>
  
  <pre><code>cv::Keypoints.octave
  cv::Keypoints.angle
  </code></pre>
  
  <p>I am having hard time to understand how I can calculate the location. </p>
  
  <p>I have found an <a href="http://www.cs.utexas.edu/~cv-fall2012/slides/fall2012_02_specific_objects.pdf" rel="nofollow noreferrer">interesting slide</a> where with only <code>one match</code> we are able to draw a bounding box:</p>
  
  <p><img src="https://i.stack.imgur.com/ejPiP.png" width="400"></p>
  
  <p>But I don't get how I could draw that bounding box with just one match. Any help?</p>