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?