title: Does a smaller reprojection error always means better calibration?
body: <p>During camera calibration, the usual advice is to use many images (>10) with variations in pose, depth, etc. 
  However I notice that usually the fewer images I use, the smaller the reprojection error. For example with 27 images, cv::calibrateCamera returns 0.23 and with just 3 I get 0.11 
  This may be due to the the fact that during calibration we are solving a least squares problem for an overdetermined system.</p>
  
  <p>QUESTIONS:</p>
  
  <ol>
  <li><p>Do we actually use the reprojection error as an absolute measure of how good a calibration is? For example, if I calibrate with 3 images and get 0.11,  and then calibrate with 27 other images and get 0.23 can we really say that "the first calibration is better"?</p></li>
  <li><p>OpenCV uses the same images both for calibration and for calculating the error. Isn't that some form of overfitting? Wouldn't it be more correct if I actually used 2 different sets -one to compute the calibration parameters and one to compute the error-? In that case, I would use the same (test) set to calculate the error for all my calibration results from different (training) sets. Wouldn't that be more fair?</p></li>
  </ol>