title: Real time keypoint detection algorithm
body: <p>I need to measure the speed a conveyor belt under a surveillance camera. After years of wearing the belt is basically texture-less, it's even difficult to see whether the belt is moving if nothing is on top it.</p>
  <p>I'm trying to solve this problem as an object tracking problem:</p>
  <ol>
  <li>Find some keypoints/objects on the belt.</li>
  <li>Track those keypoints/objects with OpenCV's median flow tracker.</li>
  <li>Inverse perspective transform and get the speed in 3D space.</li>
  </ol>
  <p>If the keypoints/objects in step 1 are given manually, step 2 &amp; 3 work very well, but I have performance issues finding keypoints automatically: keypoint detection costs 60ms+ even if I crop the images into very small ones. I tried SURF &amp; ORB implemented in OpenCV, neither one is fast enough.</p>
  <p>Are there any other faster options ?</p>