How Does OpenCV ORB Feature Detector Work?

Question

I want to implement a feature-based alignment algorithm using the ORB feature detector and extractor.
So far, I extracted the features using ORB class from OpenCV

Answer 1

UPDATE: Now it is in the OpenCV documentation, here: http://opencv.itseez.com/modules/features2d/doc/feature_detection_and_description.html#orb

A detailed description of the algorithm is found here: http://www.willowgarage.com/sites/default/files/orb_final.pdf

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It is not mentioned in OpenCV documentation but actually OpenCV has:

Two types of descriptors:

• float descriptors:
  • SIFT
  • SURF
• uchar descriptors:
  • ORB
  • BRIEF

And corresponding matchers:

• for float descriptors:
  • FlannBased
  • BruteForce<L2<float> >
  • BruteForce<SL2<float> > //since 2.3.1
  • BruteForce<L1<float> >
• for uchar descriptors:
  • BruteForce<Hamming>
  • BruteForce<HammingLUT>
  • FlannBased with LSH index //since 2.4.0

So you need to modify your code to use for example BruteForce<Hamming> matcher for ORB descriptors. It is possible to use L2 or L1 distance for matching uchar descriptors but results will be incorrect and findHomography returns unsatisfactory results.