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I am using the University of Michigan AprilTag library for localizing objects and am seeking advice for meeting my localization accuracy goals. I am using a 0.4 MegaPixel camera, on tags that are roughly 7.5 cm wide from distances of 0.1-1.5 meters away. I have used MatLab to calibrate my camera intrinsics and distortion coefficients.

Desired Outcome I would like to be able to localize tags to within 5 mm accuracy.

Observed Outcome As I move the camera relative to the tag, the localization results vary. For every 100 cm I move away from the tag, I find drift in the projected location of the tag in the world of about 10cm.

What is a reasonable expectation for the accuracy of the my localization? What actions can I take to reduce the drift I am observing?

Jonas
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Syd Shore
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2 Answers2

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If the drift mainly appears in the Z component of the TVEC and the error increases more or less linearly it is a sure sign that the focal length (fx & fy in the camera matrix) of your calibration is off.

Try the following:

  • check your calibration board: Is the size of the grid correct? Make sure that your printer does not scale the original file
  • make sure that the calibration board is fixed on a sturdy, flat surface
  • calibrate again and check if the values of fx and fy have changed (entries (0,0) and (1,1) in the camera matrix).
  • use at least 50 pictures, vary the board's angle and remove all pictures showing motion blur before calibrating
  • also check your detection parameters: You can try to activate para.cornerRefinementMethod = cv2.aruco.CORNER_REFINE_APRILTAG to improve corner accuracy (if you are using c++, adjust the command accordingly).
chris
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  • Thanks Chris! When calibrating several times, I am certainly seeing variation in the focal length results. Assuming I am able to calibrate properly, do you have an idea of what level of accuracy I can expect in tag localization with tags of size 7.5 cm at a distance ranging from 0.1-1.5 meters? – Syd Shore Mar 23 '20 at 17:04
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(too long for a comment, so I have to post it as another answer:) This will depend on the pixel size of your sensor and the focal length of your lens (which will "scale" your actual pixel size to a "projected" pixel size). As the effective resolution changes with the distance, a safe estimate would be to use the 1.5 m effective pixel value. In terms of pixels I would not trust marker corner accuracies below 0.3 px as there seems to be an issue with subpixeling accuracy, when rotating the marker (see my open question: Understanding openCV aruco marker detection/pose estimation in detail: subpixel accuracy). Tilting the marker will also degrade the accuracy as the precision of the determined rotation (rvec of the pose) is usually only within a few degrees. If small angles (say e. g. tilted only by 2°) occur, the pose might not reflect that and thus the marker will appear smaller and the distance will thus be over-estimated. In a flat setup (provided you are not using a wide angle lens) you might be able to get the 5 mm accuracy with a sensor > 5 MPx. But taking into account tilt & rotation of the marker, I am not sure if it will suffice...

chris
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