title: Find center of a fiducial marker
body: <p>I need to track four points on a series of photos of a moving object. 
  At first, I tried markers that looked like four squares of a chessboard (2 white and 2 black) and ORB detector:</p>
  
  <pre><code>import numpy as np
  import cv2
  from matplotlib import pyplot as plt
  
  img = cv2.imread('D:/workspace_Rita/Tag5.jpg',0)
  
  orb = cv2.ORB_create()
  
  # find the keypoints with ORB
  kp = orb.detect(img,None)
  kp, des = orb.compute(img, kp)
  
  img2 = cv2.drawKeypoints(img,kp,None,color=(0,255,0), flags=0)
  plt.imshow(img2),plt.show()
  </code></pre>
  
  <p>Image: <a href="http://postimg.org/image/52phl54rz/" rel="nofollow">http://postimg.org/image/52phl54rz/</a></p>
  
  <p>Аlong with the required points (centers of the markers), I got a lot of noise, so I decided to change chessboard markers to fiducial ones, drawn in ARTag style. Moreover, these markers would help identify the points, if the object rotates. Now, with the same Python code, I get:</p>
  
  <p>Image: <a href="http://postimg.org/image/f58zzrkl5/" rel="nofollow">http://postimg.org/image/f58zzrkl5/</a></p>
  
  <p>Still I have noise points detected, and I don't see an easy way to extract the coordinates of the markers centers from the keypoints mass.
  I think, I need either to adjust the sensitivity of the detector (maybe, do some pre-filtering of the image), or find another algorithm.</p>
  
  <p>I would appreciate ideas and examples, which detectors or algorithms I could use to track fiducial markers centers in the easiest way, preferring Python language and Open CV.</p>