Matching corners using the informative arc

Corners are important features in images because they typically delimit the boundaries of regions or objects. For real‐time applications, it is essential that corners are detected and matched reliably and rapidly. This study presents two related descriptors which are compatible with standard corner...

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Bibliographic Details
Main Authors: Nadia Kanwal, Erkan Bostanci, Adrian F. Clark
Format: Article
Language:English
Published: Wiley 2014-06-01
Series:IET Computer Vision
Subjects:
Online Access:https://doi.org/10.1049/iet-cvi.2013.0104
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author Nadia Kanwal
Erkan Bostanci
Adrian F. Clark
author_facet Nadia Kanwal
Erkan Bostanci
Adrian F. Clark
author_sort Nadia Kanwal
collection DOAJ
description Corners are important features in images because they typically delimit the boundaries of regions or objects. For real‐time applications, it is essential that corners are detected and matched reliably and rapidly. This study presents two related descriptors which are compatible with standard corner detectors and able to be computed and matched at video rate: one encodes the entire region within a corner, whereas the other describes only the region within an object. The advantage of encoding only the region within an object is demonstrated. The noise stability of the descriptors is assessed and compared with that of the popular binary robust independent elementary feature (BRIEF) descriptor, and the matching performances of the descriptors are compared on video sequences from hand‐held cameras and the PETS2012 database. A statistical analysis shows that performance is indistinguishable from BRIEF.
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spelling doaj.art-def539ad0e8a4c1b9749205d32506cd52023-09-15T07:15:52ZengWileyIET Computer Vision1751-96321751-96402014-06-018324525310.1049/iet-cvi.2013.0104Matching corners using the informative arcNadia Kanwal0Erkan Bostanci1Adrian F. Clark2VASE LaboratoryComputer Science and Electronic EngineeringUniversity of EssexColchesterCO4 3SQUKVASE LaboratoryComputer Science and Electronic EngineeringUniversity of EssexColchesterCO4 3SQUKVASE LaboratoryComputer Science and Electronic EngineeringUniversity of EssexColchesterCO4 3SQUKCorners are important features in images because they typically delimit the boundaries of regions or objects. For real‐time applications, it is essential that corners are detected and matched reliably and rapidly. This study presents two related descriptors which are compatible with standard corner detectors and able to be computed and matched at video rate: one encodes the entire region within a corner, whereas the other describes only the region within an object. The advantage of encoding only the region within an object is demonstrated. The noise stability of the descriptors is assessed and compared with that of the popular binary robust independent elementary feature (BRIEF) descriptor, and the matching performances of the descriptors are compared on video sequences from hand‐held cameras and the PETS2012 database. A statistical analysis shows that performance is indistinguishable from BRIEF.https://doi.org/10.1049/iet-cvi.2013.0104handheld camerasstatistical analysisPETS2012 databasehand held camerasvideo sequencesBRIEF descriptor
spellingShingle Nadia Kanwal
Erkan Bostanci
Adrian F. Clark
Matching corners using the informative arc
IET Computer Vision
handheld cameras
statistical analysis
PETS2012 database
hand held cameras
video sequences
BRIEF descriptor
title Matching corners using the informative arc
title_full Matching corners using the informative arc
title_fullStr Matching corners using the informative arc
title_full_unstemmed Matching corners using the informative arc
title_short Matching corners using the informative arc
title_sort matching corners using the informative arc
topic handheld cameras
statistical analysis
PETS2012 database
hand held cameras
video sequences
BRIEF descriptor
url https://doi.org/10.1049/iet-cvi.2013.0104
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