On the potential for facial attractiveness as a soft biometric
On the potential for facial attractiveness as a soft biometric
This paper describes the first study on whether human facial attractiveness can be used as a soft biometric feature. By using comparative soft biometrics, with ranking and classification, we show that attractiveness does have the capability to be used within a recognition framework using crowdsourcing, by using groups from the LFW dataset. In this initial study, the Elo rating system is employed to rank subjects’ facial attractiveness based on the comparative descriptions. We will show how facial attractiveness attributes can be exploited for identification purposes and can be described in the same way and can add to performance of comparative soft biometrics attributes. Attractiveness does not appear to be as powerful as gender for recognition. It does however increase recognition capability and it is interesting that a perceptual characteristic can improve performance in this way.
Comparative Soft Biometrics, face recognition, Facial Attractive-ness, Facial Attributes, Ranking.
516-528
Alnamnakani, Moneera, Habeeb
2b25ae04-fba2-43c3-8d91-add71e2718c5
Mahmoodi, Sasan
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Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Alnamnakani, Moneera, Habeeb
2b25ae04-fba2-43c3-8d91-add71e2718c5
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Alnamnakani, Moneera, Habeeb, Mahmoodi, Sasan and Nixon, Mark
(2019)
On the potential for facial attractiveness as a soft biometric.
Bebis, G.
(ed.)
In Advances in Visual Computing. ISVC 2019.
vol. 11845,
Springer.
.
(doi:10.1007/978-3-030-33723-0_42).
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper describes the first study on whether human facial attractiveness can be used as a soft biometric feature. By using comparative soft biometrics, with ranking and classification, we show that attractiveness does have the capability to be used within a recognition framework using crowdsourcing, by using groups from the LFW dataset. In this initial study, the Elo rating system is employed to rank subjects’ facial attractiveness based on the comparative descriptions. We will show how facial attractiveness attributes can be exploited for identification purposes and can be described in the same way and can add to performance of comparative soft biometrics attributes. Attractiveness does not appear to be as powerful as gender for recognition. It does however increase recognition capability and it is interesting that a perceptual characteristic can improve performance in this way.
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Moneera_FacialAttractivenessSoftBiometrics
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OnThePotentialForFacialAttractivenessAsSoftBiometrics
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Accepted/In Press date: 20 August 2019
e-pub ahead of print date: 21 October 2019
Venue - Dates:
14th International Symposium on Visual Computing, , Lake Tahoe, United States, 2019-10-07 - 2019-10-09
Keywords:
Comparative Soft Biometrics, face recognition, Facial Attractive-ness, Facial Attributes, Ranking.
Identifiers
Local EPrints ID: 433572
URI: http://eprints.soton.ac.uk/id/eprint/433572
PURE UUID: a29a77a8-bc6a-4421-a1cd-b009af0903b3
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Date deposited: 28 Aug 2019 16:30
Last modified: 17 Mar 2024 05:12
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Contributors
Author:
Moneera, Habeeb Alnamnakani
Author:
Sasan Mahmoodi
Editor:
G. Bebis
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