[midjji]

Very few know the old methods. Few were trained, and deep learning started working just 5 years after classics got good and easy enough that a few people could use it for a product. So there was never the needed wave of non deep learning based computer vision students, they all went to deep learning.

Many of the libraries are not well maintained. I needed a basic homography estimation recently and asked a minion to try opencv for it before anything more advanced. He got it working, but the best inlier ratio for every feature he tried with default parameters was 3%. The images were offset by 30 pixels left right, and less than a pixel in warp and taken with different exposure time. So he used sift...

He argued he got it working and that was as good as keypoint matching got... If I hadnt happened to be the guy who needed it one step up, it could have just propagated, someone adding a shitty ekf to make it smooth, then buried in layers of heuristics and api.

[tomp]

Hey, I’m very interested in learning more about sfm, 3d reconstruction, slam etc. primarily for robotics applications (3D vision). Currently still a hobby project but I’m more than happy to throw money at it. If you’d be willing to share some wisdom or help otherwise, shoot me an email!

[midjji]

Will do