In Chapter 4, Controlling a Phone App with Your Suave Gestures, we used the Good Features to Track algorithm to detect trackable features in images. OpenCV offers implementations of several more feature-detection algorithms. Two of the other algorithms, called minimum eigenvalue corners and Harris Corners, are precursors to Good Features to Track, which improves upon them. An official tutorial illustrates the use of eigenvalue corners and Harris Corners in a code sample at https://docs.opencv.org/master/d9/dbc/tutorial_generic_corner_detector.html.
Some of the other, more-advanced feature-detection algorithms in OpenCV are named FAST, ORB, SIFT, SURF, and FREAK. Compared to Good Features to Track, these more-advanced alternatives evaluate a much larger set of potential features, at a much greater computational cost. They are overkill...
