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2019-12-03 08:35:04 -0600 | marked best answer | Homography estimation when feature matching fails Hi all, I'm pretty new to openCV and CV in general. I want to align images of football pitches to a basic template of the pitch. I've managed to find a reasonable way of processing the full pitch images to leave me with pretty much just the pitch markings and I now have what appears to be a fairly straightforward registration problem. I can't get it to work. I've tried orb and akaze feature matching but it doesn't work at all. Both pick up good features (mostly the curved portions like the centre circle and the D) but the matching is awful. I was using brute force matching with Hamming distance and then selecting say the top 10% of matches to estimate the homography. What's the best approach here? I was thinking I could use a hough transform to find the centre circle in each image and match those, but the full centre circle won't always be in the target image. Here are two example images: Pitch template: Processed image to align: |
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2019-12-03 08:19:18 -0600 | answered a question | Homography estimation when feature matching fails I ended up coming up with a bit of a convoluted way of doing this that seems to work OK. Use opencv's fast line detec |
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2019-10-18 03:54:16 -0600 | commented question | Homography estimation when feature matching fails I can, but I need to do this for quite a few frames so I need something automatic really. I wouldn't mind manually selec |
2019-10-17 16:00:40 -0600 | commented question | Homography estimation when feature matching fails Thanks for taking a look! No other way using ellipse/line detection? Or a regression approach where I try to minimise th |
2019-10-17 13:48:06 -0600 | asked a question | Homography estimation when feature matching fails Homography estimation when feature matching fails Hi all, I'm pretty new to openCV and CV in general. I want to align i |