How do they do it? That's what I want to know.
It really does work - and even finds rotated images.
It really does work - and even finds rotated images.
Maybe it calculates some kind of hash on every image, an then it looks for images that are at a distance lower than n to such hash? But I don't know any hashing system for images that could work this way... could anyone explain?
Edit: a fingerprint is mentioned in the video, so I guess there is some kind of hashing system after all.
An idea I had was some sort of contour tracing, that will track each contrast path in the image, and then create a code the defines it in terms of changes in direction of the contour - that will handle rotations.
You make a large number of those for each contour in the image. Then match new images against that list.