Increasing Recall rate for SIFT Is there a better way to increase Recall Rate when using SIFT features?
I am thinking a way to replace the NN1/NN2 ratio to account for slightly distorted objects.
Moving towards clustering and using BOW(Bag Of Words) seems a way but I need to do one-on-one match of objects in images rather than training and learning. This refrains me from thinking towards BOW.

Anybody got any idea?
With slight modification you might want to use RootSift:

http://www.robots.ox.ac.uk/~vgg/publications/2012/Arandjelovic12/arandjelovic12.pdf

Also the other steps in the paper will guide to improve the recall rate.

Cheers,