/ArUco-markers-with-OpenCV-and-Python

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ArUco-markers-with-OpenCV-and-Python

What is ArUco

  • Similar to AprilTags, ArUco markers are 2D binary patterns that computer vision algorithms can easily detect.

ArUco Usability

  1. Camera calibration
  2. Object size estimation
  3. Measuring the distance between camera and object
  4. 3D position
  5. Object orientation
  6. Robotics and autonomous navigation
  7. etc.

ArUco over AprilTag

  1. ArUco markers are built into the OpenCV library via the cv2.aruco submodule (i.e., we don’t need additional Python packages).
  2. The OpenCV library itself can generate ArUco markers via the cv2.aruco.drawMarker function.
  3. There are online ArUco generators that we can use if we don’t feel like coding (unlike AprilTags where no such generators are easily found).
  4. There are ROS (Robot Operating System) implementations of ArUco markers.
  5. And from an implementation perspective, ArUco marker detections tend to be more accurate, even when using the default parameters.

References

  1. https://www.pyimagesearch.com/2020/12/14/generating-aruco-markers-with-opencv-and-python/
  2. https://www.pyimagesearch.com/2020/12/21/detecting-aruco-markers-with-opencv-and-python/
  3. https://www.pyimagesearch.com/2020/12/28/determining-aruco-marker-type-with-opencv-and-python/