A Modern Computer Vision Library
SIFT paper refers to: Distinctive Image Features from Scale-Invariant Keypoints, David G. Lowe
The current implementation in ccv was largely influenced by VLFeat: http://www.vlfeat.org/
There is a sample program under bin/siftmatch that at your disposal, to run it, just simply type:
./siftmatch ../samples/book.png ../samples/scene.png
The output may not be most interesting thing for you, want to see some images? There is siftdraw.rb script to do that, pipe the command:
./siftmatch ../samples/book.png ../samples/scene.png | ./siftdraw.rb ../samples/book.png ../samples/scene.png output.png
Check out output.png, there are interesting lines between the book and the scene.
There is a way to show more amazing result, but with a little external help, a program called homest (http://www.ics.forth.gr/~lourakis/homest/), it may requires levmar program (http://www.ics.forth.gr/~lourakis/levmar/) as well. compile homest until you get the homest_demo binary somewhere, and pipe the command like this:
./siftmatch ../samples/book.png ../samples/scene.png | ./siftdraw.rb ../samples/book.png ../samples/scene.png output.png <directory to homest>/homest_demo
You see, somehow, SIFT recognized the book in the scene, amazing, ah?
I haven’t decided yet that if I need to include some functions like ccv_find_homography in the future release, homest is a good research package but for industrial use, I have some doubts.