Moderator: Computer Vision
But it seems that you do not find the best homography.
If you visualize your result without blending, that should be clear.
Your homography points are very localized, therefore small errors in the estimation might become more severe.
we modified our ransac implementation so that it not only tries to get the most inliers, but also maximizes the distance between the points.
Unfortunately though, the results are still the same:
Are we the only ones to experience this problem?
Oh btw. here is the output of displaymatches for the images above.
Code: Alles auswählen
Found 20 inliers! Match 1: dist=0.27914 Match 2: dist=0.47025 Match 3: dist=0.71193 Match 4: dist=0.87769 Match 5: dist=0.89023 Match 6: dist=0.98987 Match 7: dist=1.0719 Match 8: dist=1.1897 Match 9: dist=1.3035 Match 10: dist=1.3532 Match 11: dist=1.4211 Match 12: dist=1.5414 Match 13: dist=1.5612 Match 14: dist=1.5863 Match 15: dist=1.74 Match 16: dist=1.806 Match 17: dist=1.8194 Match 18: dist=1.8287 Match 19: dist=1.8701 Match 20: dist=1.9939
A distance of 2 is fine, but I think there should be a lot more inliers.
So either you have too few inliers from the start or you do not find all of them.
When visualizing your best pairs, how many inliers do you count ?
With my parameter setting I have a rather large fraction of inliers.
I get that result with the settings provided (window size 50).
You can also compare your result with the pictures from the slides presented at the exercise last week.
If you count less inliers your problem should be in the first part of the exercise.
Otherwise your ransac (exiting too early?) or homography estimation has problems.
It's amazing how "good" our results were though, given the severity of this mistake.