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Which feature detection algorithm does cv2.Stitcher() use?

Time:11-19

I just learnt about SIFT, ORB & SURF algorithms and how they are used for feature detection & extraction, and Homography & RANSAC techniques used in Image Fusion. While SIFT & SURF algorithms are patented and mostly have better accuracy (source1, source2), ORB algorithm is lightweight and Open Sourced.

OpenCV Stitcher function (documentation) is built such that it can be used even without knowing the entire image stitching pipeline.

So I am curious to know, which algorithms are used (especially for feature detection & extraction) in the cv2.Stitcher class? Also is it possible to choose different algorithms other than the default ones, used in its implementation?

CodePudding user response:

The stitcher class uses ORB by Default:

stitcher->setFeaturesFinder(ORB::create());

in stitcher.cpp

You can use stitching_detailed.py/stitching_detailed.cpp or the stitching python package to play around with different detectors

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