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The difference between the keypoint approach and for example the BOW approach is the reduction of the descriptor itself. At keypoint approaches all found keypoints must be matched with each keypoint found in the second image to look for occurences. BOW is an approach that generates a short notebook description of a database item and then tries to find those descriptions (a very short explanation of BOW here ... I know) in the new image. This mean less validations need to happen and thus it should work faster. However BOW takes time to train, is not that rotation invariant. Take a look at this post.
