Features from accelerated segment test: Difference between revisions

Revision as of 07:49, 6 October 2015

Revision as of 15:30, 27 April 2016

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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. 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 [[Scale-invariant feature transform|SIFT]], [[Corner detection#The SUSAN corner detector|SUSAN]] and [[Harris affine region detector|Harris]] detectors. Moreover, when machine learning methodtechniques isare applied, a bettersuperior performance couldin beterms achievedof which takes lesscomputation time and computational 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 ==