Howtosignalprocessing
- How does the ORB algorithm work?
- What is the advantage of ORB oriented fast and rotated brief over SURF speeded up robust features?
- Is ORB better than SIFT?
- Are ORB features scale invariant?
How does the ORB algorithm work?
ORB uses BRIEF descriptors but as the BRIEF performs poorly with rotation. So what ORB does is to rotate the BRIEF according to the orientation of keypoints. Using the orientation of the patch, its rotation matrix is found and rotates the BRIEF to get the rotated version.
What is the advantage of ORB oriented fast and rotated brief over SURF speeded up robust features?
ORB performs as well as SIFT on the task of feature detection (and is better than SURF) while being almost two orders of magnitude faster. ORB builds on the well-known FAST keypoint detector and the BRIEF descriptor. Both of these techniques are attractive because of their good performance and low cost.
Is ORB better than SIFT?
We showed that ORB is the fastest algorithm while SIFT performs the best in the most scenarios. For special case when the angle of rotation is proportional to 90 degrees, ORB and SURF outperforms SIFT and in the noisy images, ORB and SIFT show almost similar performances.
Are ORB features scale invariant?
ORB features are invariant to scale, rotation and limited affine changes. S. Leutenegger et al. put forward Binary Robust Invariant Scalable Keypoints (BRISK) in 2011 [18], which detects corners using AGAST algorithm and filters them with FAST Corner score while searching for maxima in the scale space pyramid.
