Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/5021
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dc.contributor.authorPrakash, Suryaen_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-17T15:36:31Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-17T15:36:31Z-
dc.date.issued2014-
dc.identifier.citationPrakash, S., & Gupta, P. (2014). Human recognition using 3D ear images. Neurocomputing, 140, 317-325. doi:10.1016/j.neucom.2014.03.007en_US
dc.identifier.issn0925-2312-
dc.identifier.otherEID(2-s2.0-84901501417)-
dc.identifier.urihttps://doi.org/10.1016/j.neucom.2014.03.007-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/5021-
dc.description.abstractThis paper proposes an ear recognition technique which makes use of 3D along with co-registered 2D ear images. It presents a two-step matching technique to compare two 3D ears. In the first step, it computes salient 3D data points from 3D ear images with the help of local 2D feature points of co-registered 2D ear images. Subsequently, it uses these salient 3D points to coarsely align 3D ear images. In the second step, it performs final matching of coarsely aligned 3D ear images by using a Generalized Procrustes Analysis (GPA) and Iterative Closest Point (ICP) based matching technique (GPA-ICP). The proposed technique has been tested on 1780 images of 404 subjects (two or more images per subject) of University of Notre Dame public database-Collection J2 (UND-J2) which consists of co-registered 2D and 3D ear images with scale and pose variations. It has achieved a verification accuracy of 98.30% with an equal error rate of 1.8%. © 2014 Elsevier B.V.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.sourceNeurocomputingen_US
dc.subjectBiometricsen_US
dc.subject3D ear recognitionen_US
dc.subjectGeneralized procrustes analysisen_US
dc.subjectHuman recognitionen_US
dc.subjectIterative closest pointen_US
dc.subjectIterative Closest Pointsen_US
dc.subjectLocal featureen_US
dc.subjectMatching techniquesen_US
dc.subjectUniversity of Notre Dameen_US
dc.subjectFace recognitionen_US
dc.titleHuman recognition using 3D ear imagesen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Computer Science and Engineering

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