Oriented FAST and rotated BRIEF
Oriented FAST and rotated BRIEF (ORB) is a fast robust local feature detector, first presented by Ethan Rublee et al. in 2011,[1] that can be used in computer vision tasks like object recognition or 3D reconstruction. It is based on the FAST keypoint detector and a modified version of the visual descriptor BRIEF (Binary Robust Independent Elementary Features). Its aim is to provide a fast and efficient alternative to SIFT.
| Feature detection |
|---|
| Edge detection |
| Corner detection |
| Blob detection |
| Ridge detection |
| Hough transform |
|
| Structure tensor |
| Affine invariant feature detection |
| Feature description |
| Scale space |
See also
- Scale-invariant feature transform (SIFT)
- Gradient Location and Orientation Histogram
- LESH - Local Energy based Shape Histogram
- Blob detection
- Feature detection (computer vision)
References
External links
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