Hello,
in a project I'm using SURF to extract keypoints from a set of near similar images.
The images are near similar, so they have a lot of similar keypoints and a few keypoints that are different.
My goal is to find groups of keypoints that matched by all images
is there an idea how to solve this?
I can't use kmeans, because i doesn't know something about the `k`
**UPDATE**
My current approach is using a `bruteforce-matcher`to find the good matches of each image.
I compare all images with each other. But it is very difficut to save the intersection from all good matches of all images. Is there a datastructure that can help me to solve this problem?
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