 | 1 | initial version |
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
| | 2 | No.2 Revision |
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-matcherto 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?
