Machine Learning in FAST corner detector

1. What is fast corner detector?
2. Which of the following is an algorithm for corner detection?
3. How is the fast detector different from the Harris corner detector?
4. What is fast feature detector?

What is fast corner detector?

Features from Accelerated Segment Test (FAST) is a corner detection algorithm. It detects corners on an input image, returning their coordinates. These corners can then be used as feature keypoints for tracking. The main advantage of using FAST is its computational efficiency, thus its name.

Which of the following is an algorithm for corner detection?

The Förstner corner detector

To achieve an approximate solution, the Förstner algorithm solves for the point closest to all the tangent lines of the corner in a given window and is a least-square solution.

How is the fast detector different from the Harris corner detector?

The Harris algorithm uses more hardware resources than the FAST algorithm but can detect corners that the FAST algorithm might not find.

What is fast feature detector?

Features from accelerated segment test (FAST) is a corner detection method, which could be used to extract feature points and later used to track and map objects in many computer vision tasks. The FAST corner detector was originally developed by Edward Rosten and Tom Drummond, and was published in 2006.