Content deleted Content added
Happymacaron (talk | contribs) →Segment test detector: Add image; Format math expressions. |
Citation bot (talk | contribs) Alter: title, template type. Add: isbn, doi, pages, volume, series, chapter, s2cid. Removed URL that duplicated unique identifier. Formatted dashes. Some additions/deletions were actually parameter name changes. | You can use this bot yourself. Report bugs here. | Activated by AManWithNoPlan | All pages linked from User:AManWithNoPlan/sandbox2 | via #UCB_webform_linked |
||
Line 1:
'''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
|last1=Rosten |first1=Edward
|last2=Drummond |first2=Tom
|title=Computer Vision – ECCV 2006
|s2cid=1388140
|date=2006
|
|series=Lecture Notes in Computer Science
|volume=3951
|pages=430–443
|doi=10.1007/11744023_34
|isbn=978-3-540-33832-1
}}
</ref> The most promising advantage of the FAST [[corner detector]] is its computational efficiency. Referring to its name, it is indeed 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.
| |||