I solved this a while ago, apologies for the year delay. In the python OpenCV 2.1 I was using, and the newer version 3.0.0-dev, I have verified that to get the pose of the camera in the global frame you must: _, rVec, tVec = cv2.solvePnP(objectPoints, imagePoints, cameraMatrix, distCoeffs) Rt = cv2.Rodrigues(rvec) R = Rt.transpose() … Read more
This is nowhere near my cup of tea so handle with extreme prejudice and also far form solution just some start point hints… First of all we need to define some constraints/assumptions in order to make this to work. user selects 4 lines representing 2 perpendicular planes and these 2 QUADs have the same height … Read more
I think you may be thinking of tvecs_new as the camera position. Slightly confusingly that is not the case! In fact it is the position of the world origin in camera co-ords. To get the camera pose in the object/world co-ords, I believe you need to -np.matrix(rotation_matrix).T * np.matrix(tvecs_new) And you can get the Euler … Read more
If you got extrinsic parameters then you got everything. That means that you can have Homography from the extrinsics (also called CameraPose). Pose is a 3×4 matrix, homography is a 3×3 matrix, H defined as H = K*[r1, r2, t], //eqn 8.1, Hartley and Zisserman with K being the camera intrinsic matrix, r1 and r2 … Read more
Given your configuration, errors of 20-40mm at the edges are average. It looks like you’ve done everything well. Without modifying camera/system configuration, doing better will be hard. You can try to redo camera calibration and hope for better results, but this will not improve them alot (and you may eventually get worse results, so don’t … Read more
Hmm, are you looking for “handsome” or “accurate”? Camera calibration is one of the very few subjects in computer vision where accuracy can be directly quantified in physical terms, and verified by a physical experiment. And the usual lesson is that (a) your numbers are just as good as the effort (and money) you put … Read more