iago-suarez / beblid Goto Github PK

Excuse me. Thanks for sharing the excellent work.

When I use BEBLID to extract descriptors for keypoints from cv::goodFeaturesToTrack(), I find that many descriptors are all ones. I have tried all optional parameters but get similar results.

Is it related to training process? Would you please help me with my confusion? Thanks a lot.

Thank you for sharing this wonderful work!
I am testing your results on HPatches, however I am not sure which keypoint scale (sampling window) you utilized when testing BEBLID descriptor. I noticed that you have mentioned a recommended scale for different keypoint (so I set 6.75 for hpatches). But the resulting matching mAP is only 0.13.

So what are the scale settings for you when evaluating on hpatches? Thanks in advance!

We have found a problem with the scale of the time measurements in the original paper "Suárez, I., Sfeir, G., Buenaposada, J. M., & Baumela, L. (2020). BEBLID: Boosted efficient binary local image descriptor. Pattern Recognition Letters, 133, 366-372.". The time measurements have been scaled down by a constant factor around x13 due to a bug in the experiment source code. For example, the real execution times for BEBLID-512 in the images of Oxford dataset with sizes between (765x512) and (1000x700) is not 0.21 ms as pointed out in the paper but 0.21 x13 ms = 2.73 ms . This is also the case for the other descriptors and therefore the relevance and conclusions of the paper remains the same.

I am curious to know if the BEBLID descriptor can be used with a GFFT-detector in opencv? :)