How to implement SIFT (Scale-invariant feature transform) for 3D image in Python?

How to implement SIFT (Scale-invariant feature transform) for 3D image in Python?



I saw many examples of SIFT for 2-dimensional image only: http://docs.opencv.org/3.1.0/da/df5/tutorial_py_sift_intro.html. But in Wikipedia there is written that SIFT may be applied for "3D modelling" as well. Please help me to find examples for 3-dimensional image in Python, or provide me the ones of your own. I need to find locations of Amino Acids within given protein (creo EM scan), and I want to compare precision of SIFT compared to other heuristics calculations.





I also have this question, for openCV. As far as I can tell it may need to be coded from scratch.
– eldorz
Sep 7 '16 at 3:51





1 Answer
1



If you need to do some 3D program, I suggest you to look at this great library: Point Cloud Library (PCL). However, I think you might need to program in C++ mainly.



If you really like to code in Python, you could look at the python-pcl. It is a python binding to the subset of actual Point Cloud Library.



And if you like to find how to use 3D keypoint detectors, including 3D sift, you can look at this page here and a nice tutorial here.






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