Add BEBLID local feature descriptor#2774
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alalek merged 4 commits intoopencv:masterfrom Dec 9, 2020
iago-suarez:master
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Add BEBLID local feature descriptor#2774alalek merged 4 commits intoopencv:masterfrom iago-suarez:master
alalek merged 4 commits intoopencv:masterfrom
iago-suarez:master
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alalek
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Great contribution!
Please take a look on comments below.
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| BEBLID::SIZE_512_BITS or BEBLID::SIZE_256_BITS. | ||
| */ | ||
| CV_WRAP static Ptr<BEBLID> create(float scale_factor, | ||
| BEBLID::BeblidSize n_bits = BEBLID::SIZE_512_BITS); |
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OK, lets use int here for now.
I filled Java binding generator bug here: opencv/opencv#19056
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Perfect, I changed the code to use int again
…ng descriptors when no keypoints are detected.
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Well done! Thank you for contribution 👍
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Thanks for your review and comments @alalek , it's a pleasure to contribute! 😃 |
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Merge with extra: opencv/opencv_extra#827
BEBLID is a efficient binary descriptor learned with boosting. In several benchmarks it has proved to largely improve other binary descriptors like ORB or BRISK with the same efficiency. BEBLID describes using the difference of mean gray values in
different regions of the image around the KeyPoint, the descriptor is specifically optimized for
image matching and patch retrieval addressing the asymmetries of these problems.
This Pull Request ports the original code to OpenCV. The article explaining all the details and comparing the descriptor in several tasks can be found here.
Testing this implementation with the code of the A-KAZE tutorial, we have found that, detecting 10000 keypoints with ORB and describing with BEBLID obtains 561 inliers (75%) whereas describing with ORB obtains only 493 inliers (63%).
Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
Patch to opencv_extra has the same branch name.