snavely
commented
9 years ago Hi Oleg,
You are right that binary descriptors are a whole different kind of beast. Is there a particular reason you want to go with them? Speed / memory? Anyhow, maybe start with looking at Vincent Lepetit's work -- he's looked at creating binary descriptors as well as matching them. ( http://cvlabwww.epfl.ch/~lepetit/). Also take a look at this paper: http://www.cs.ubc.ca/~lowe/papers/12mujaCRV.pdf.
Best, Noah
On Thu, Dec 4, 2014 at 9:10 PM, Oleg Alexandrov notifications@github.com wrote:
Noah,
VocabTree2 works very well for me with SIFT descriptors, as it was designed. I am looking for a solution using binary descriptors, such as BRISK. From what I've been reading, it appears that VocabTree2 may not generalize well to binary descriptors since it uses k-means and Euclidean distance, while for binary descriptors the Hamming distance and other ways of clustering may be more appropriate. I wonder if you have any insights on this, and if by chance any pointers to relevant software. Thank you.
— Reply to this email directly or view it on GitHub https://github.com/snavely/VocabTree2/issues/5.
oleg-alexandrov
Noah,
VocabTree2 works very well for me with SIFT descriptors, as it was designed. I am looking for a solution using binary descriptors, such as BRISK. From what I've been reading, it appears that VocabTree2 may not generalize well to binary descriptors since it uses k-means and Euclidean distance, while for binary descriptors the Hamming distance and other ways of clustering may be more appropriate. I wonder if you have any insights on this, and if by chance any pointers to relevant software. Thank you.