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. FAST corner detector was originally developed by Edward Rosten and Tom Drummond, and published in 2006. The most promising advantage of the FAST corner detector is its computational efficiency. Referring to its name, it is fast and indeed it is faster than many other well-known feature extraction methods, such as difference of Gaussians (DoG) used by the SIFT, SUSAN and Harris detectors. Moreover, when machine learning techniques are applied, superior performance in terms of computation time and resources can be realised. The FAST corner detector is very suitable for real-time video processing application because of this high-speed performance. from wiki
How to usage: https://github.com/lafin/fast-brief
port of the code