SuperGluePretrainedNetwork
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magicleap
Bad homography transformation obtained from superglue matchpoints. Help!
Hi,
I am using SuperPoint and SuperGlue to extract features and match them to compute homography between two images but the matchpoints seem to be performing worse than SIFT-FAST.
The left image is 1080x1088 and right is 1920x1440. They are captured using two different sensors.
The matchpoints look good but if I use them to compute homography using cv2.findhomography(), this is what I get
I have tried modifying a lot of parameters but the homography I get using the matchpoints is no up to the mark. I am using "outdoor" superglue to accommodate for multiple sensors whose intrinsic matrices are unknown.
Here is the wrap using SIFT and FAST which looks waaaaay better
I want to get a decent homography transformation using SuperPoint and SuperGlue. Any idea on what the issue is and how I can fix it? Note: the goal is NOT to retrain either of the networks.
All help is much appreciated. Thanks!
The correspondences look fine. The issue is likely due to an incorrect use of cv2.findhomography - I've used it in the past without any problem.
The correspondences look fine. The issue is likely due to an incorrect use of
cv2.findhomography- I've used it in the past without any problem.
Why are there so few points that can be matched
@Skydes , have you used them when the image's keypoints in the world space are not planar? I recently re-learnt that homography will only work when the points are on a planar surface and in my case, I have points being picked from two different planar surfaces.
@foxkw , the threshold for keypoint match is high. I am after high quality matches. Even though I am using a match threshold of 0.95, I still get some false positives. Do you have any experience with this?
NO. but I found that the number of points you detected is also very small, and I also encountered this situation; I don't know whether this is the cause; I found that the number of matches of the superpoint model I trained with superglue after homography transformation is far less than the official result. I wonder if you have encountered and solved this phenomenon
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