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'''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.<ref>
{{cite journal |last1=Rosten |first1=Edward |last2=Drummond |first2=Tom |date=2006 |title=Machine Learning for High-speed Corner Detection |url=https://pdfs.semanticscholar.org/e3d7/f693bf2d3510a0557cda52c7547820fbef97.pdf }} </ref> 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 [[Scale-invariant feature transform|SIFT]], [[Corner detection#The SUSAN corner detector|SUSAN]] and [[Harris affine region detector|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. == Segment test detector ==
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