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Gender and kinship by model-based ear biometrics

Gender and kinship by model-based ear biometrics
Gender and kinship by model-based ear biometrics
Many studies in biometrics have shown how identity can be determined, including by images of ears. We show we can model an ear and how the gender appears to often be manifest in the ear structures, as is kinship or family relationship. We describe a new model-based approach for viewpoint correction and ear description to enable this analysis. We show that with the new technique having satisfactory basic recognition capability (recognizing individuals with performance similar to state of art), gender can achieve 67.2% and kinship 40.4% rank 1 recognition on ears from subjects with unconstrained pose.
model-based, kinship verification, gender classification, geometric features
Meng, Di
ec8d62a6-c99c-4fbf-93e3-ff705c6a8279
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Meng, Di
ec8d62a6-c99c-4fbf-93e3-ff705c6a8279
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Meng, Di, Mahmoodi, Sasan and Nixon, Mark (2019) Gender and kinship by model-based ear biometrics. 18th International Conference of the Biometrics Special Interest Group, , Darmstadt, Germany. 18 - 20 Sep 2019. 9 pp . (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

Many studies in biometrics have shown how identity can be determined, including by images of ears. We show we can model an ear and how the gender appears to often be manifest in the ear structures, as is kinship or family relationship. We describe a new model-based approach for viewpoint correction and ear description to enable this analysis. We show that with the new technique having satisfactory basic recognition capability (recognizing individuals with performance similar to state of art), gender can achieve 67.2% and kinship 40.4% rank 1 recognition on ears from subjects with unconstrained pose.

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biosig19 - Accepted Manuscript
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More information

Accepted/In Press date: 19 July 2019
Venue - Dates: 18th International Conference of the Biometrics Special Interest Group, , Darmstadt, Germany, 2019-09-18 - 2019-09-20
Keywords: model-based, kinship verification, gender classification, geometric features

Identifiers

Local EPrints ID: 433571
URI: http://eprints.soton.ac.uk/id/eprint/433571
PURE UUID: 04266f49-f2c5-4b1a-959b-51ff34dfc39f
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 28 Aug 2019 16:30
Last modified: 17 Mar 2024 02:33

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Contributors

Author: Di Meng
Author: Sasan Mahmoodi
Author: Mark Nixon ORCID iD

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