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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. 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 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 b

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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. 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 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. (en)
  • Features from Accelerated Segment Test (FAST), que l'on peut traduire par caractéristiques issues de tests accélérés de segments, est un algorithme de détection de caractéristique et un descripteur, présenté par des chercheurs de l'université de Cambridge pour la première fois en 2006. Il est utilisé dans le domaine de vision par ordinateur, pour des tâches de détection d'objet ou de . L'algorithme fonctionne en deux étapes : dans la première étape, un test de segment basé sur les luminosités relatives est appliqué à chaque pixel de l'image traitée ; la deuxième étape permet d'affiner et de limiter les résultats par la méthode dite de non-maximum suppression. (fr)
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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. 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 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 b (en)
  • Features from Accelerated Segment Test (FAST), que l'on peut traduire par caractéristiques issues de tests accélérés de segments, est un algorithme de détection de caractéristique et un descripteur, présenté par des chercheurs de l'université de Cambridge pour la première fois en 2006. Il est utilisé dans le domaine de vision par ordinateur, pour des tâches de détection d'objet ou de . (fr)
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  • Features from accelerated segment test (en)
  • Features from Accelerated Segment Test (fr)
  • Ознаки з прискореної сегментної перевірки (uk)
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