Inconsistent results with `recoverPose`

[jackCaster]

Hi all, thank you for getting back to me. I will try to clarify some of the confusion.

@Steve_in_Denver

I interpreted the 0.03 reprojection error as being from calibrateCamera(), not findEssentialMat(). Upon re-reading, it’s not clear to me what the 0.03 value represents.

The camera is a webcam (Logitech C920). The 0.03 is the reprojection error from cv.projectPoints() right after I calibrated the camera. I followed the tutorial OpenCV: Camera Calibration. I used 18 pictures of a grid taken inside. The grid pattern is this one. The pics of the grid look like

.

Perhaps I need more variation?

@Steve_in_Denver

If I understand correctly, OP is taking two sequential frames with no camera movement. So the images are nearly identical, but not the same actual image (difference being sensor noise etc.).

Correct. I am working with a test video, but in the beginning of this video the camera is still. I am comparing the frame with the one right before. The frames are basically identical a part from some sensor noise.

@Steve_in_Denver

My hunch is that step 3 is where the problem lies (SIFT + Flann + “keep the ones that are closer”), and that the matchpoint set contains errors.

I retain the good matches using this procedure that I found in the OpenCV doc (unfortunately new forum users cannot post more than 1 link)

matches = matcher.knnMatch(descriptors0, descriptors1, k=2)
good_matches = []
for m, n in matches:
   if m.distance < 0.6 * n.distance:
      good_matches.append(m)

@Steve_in_Denver

If it were me, I’d be scrutinizing the matches from a “bad” image pair and / or running findEssentialMat on subsets of the matches.

I will try what you suggested. I will also clean up the code so I can post it. Thank you both!