The distance estimated (in cm: Because input size of ArUco Markers in cm too) using the code line after importing math module:

numpy.sqrt(tvecs[0][0][0]**2 + tvecs[0][0][1]**2 + tvecs[0][0][2]**2) where tvecs represent the translation vectors of the ArUco Marker obtained using the OpenCV Function in Python:

cv.estimateSinglePosemarkers(mtx, dst, .. ) alongside rvecs(Rotation Vectors) obtained using Camera Matrix(mtx) and Distortion Coefficent(dst) in turn obtained by performing Camera Calibration (using a piece of code and a bunch of images of a checkerboard held at different angles)

In contrast, the distance estimated (in cm) using the code line after importing math module:

math.sqrt(tvecs[0][0][0]**2 + tvecs[0][0][1]**2 + tvecs[0][0][2]**2) is pretty accurate(<<10%) at larger distances.

Has anybody run into this before? If so, why does using a different library make such a huge difference?



Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Browse other questions tagged or ask your own question.