opencv Freak - Can I use Freak feature descriptor with BOW?

Question

I am trying to use Freak in opencv to detect features and extract descriptors, then build my BOW vocabulary and for each image use the vocabulary to match with BOW. You know, the whole thing. I know BOW can be used with other descriptors like SIFT or SURF, it is not clear to me if Freak descriptors, which are binary, can be used with BOW. More specifically, when opencv builds a BOW vocabulary, it uses k-means cluster. It is not clear to me what distance function the k-means cluster algorithm uses. For binary descriptors like Freak, Hamming distance seems to be the only choice.

It looks to me opencv k-means only uses euclidean distance when calculating distance, bummer. Looks like I have to build my own k-means and my own vocabulary matching. Any smart people out there know a workaround?

Thanks!

Answer 1

I read on a paper that Freak is not easy to be used. Here is the excerpt form the paper "....These algorithms cannot be easily used in many retrieval algorithms because they must be compared with a Hamming distance, which is not easily adapted to accelerated search structures such as vocabulary trees or Approximate Nearest Neighbors (ANN)...." (ORB ,FREAK and BRISK)

Answer 2

FREAK works with locality sensitive hashing. You can use it with FLANN (Fast approximate nearest neighbors) included in OpenCV.

For the BOW, only the first 5, 6, 7, 8 bytes of the descriptor might be sufficient to construct the tree.