Understanding types of feature detection and matching
A number of algorithms can be used to detect and describe features, and we will explore several of them in this section. The most commonly used feature detection and descriptor extraction algorithms in OpenCV are as follows:
- Harris: This algorithm is useful for detecting corners.
- SIFT: This algorithm is useful for detecting blobs.
- SURF: This algorithm is useful for detecting blobs.
- FAST: This algorithm is useful for detecting corners.
- BRIEF: This algorithm is useful for detecting blobs.
- ORB: This algorithm stands for Oriented FAST and Rotated BRIEF. It is useful for detecting a combination of corners and blobs.
Matching features can be performed with the following methods:
- Brute-force matching
- FLANN-based matching
Spatial verification can then be performed with homography.
We have just introduced a lot of new terminology and algorithms. Now, we will go over their basic definitions.
Defining features
What is a feature, exactly...