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Unconstrained human identification using comparative facial soft biometrics

Unconstrained human identification using comparative facial soft biometrics
Unconstrained human identification using comparative facial soft biometrics
Soft biometrics are attracting a lot of interest with the spread of surveillance systems, and the need to identify humans at distance and under adverse visual conditions. Comparative soft biometrics have shown a significantly better impact on identification performance compared to traditional categorical soft biometrics. However, existing work that has studied comparative soft biometrics was based on small datasets with samples taken under constrained visual conditions. In this paper, we investigate human identification using comparative facial soft biometrics on a larger and more realistic scale using 4038 subjects from the View 1 subset of the LFW database. Furthermore, we introduce a new set of comparative facial soft biometrics and investigate the effect of these on identification and verification performance. Our experiments show that by using only 24 features and 10 comparisons, a rank-10 identification rate of 96.98% and a verification accuracy of 93.66% can be achieved.
Almudhahka, Nawaf Y.
929b4dbb-016d-44bb-9755-b9e0adb6ded0
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Hare, Jonathon S.
65ba2cda-eaaf-4767-a325-cd845504e5a9
Almudhahka, Nawaf Y.
929b4dbb-016d-44bb-9755-b9e0adb6ded0
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Hare, Jonathon S.
65ba2cda-eaaf-4767-a325-cd845504e5a9

Almudhahka, Nawaf Y., Nixon, Mark S. and Hare, Jonathon S. (2016) Unconstrained human identification using comparative facial soft biometrics At BTAS 2016: IEEE 8th International Conference on Biometrics Theory, Applications and Systems, United States. 06 - 09 Sep 2016. 6 pp.

Record type: Conference or Workshop Item (Paper)

Abstract

Soft biometrics are attracting a lot of interest with the spread of surveillance systems, and the need to identify humans at distance and under adverse visual conditions. Comparative soft biometrics have shown a significantly better impact on identification performance compared to traditional categorical soft biometrics. However, existing work that has studied comparative soft biometrics was based on small datasets with samples taken under constrained visual conditions. In this paper, we investigate human identification using comparative facial soft biometrics on a larger and more realistic scale using 4038 subjects from the View 1 subset of the LFW database. Furthermore, we introduce a new set of comparative facial soft biometrics and investigate the effect of these on identification and verification performance. Our experiments show that by using only 24 features and 10 comparisons, a rank-10 identification rate of 96.98% and a verification accuracy of 93.66% can be achieved.

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More information

e-pub ahead of print date: 6 September 2016
Venue - Dates: BTAS 2016: IEEE 8th International Conference on Biometrics Theory, Applications and Systems, United States, 2016-09-06 - 2016-09-09
Organisations: Vision, Learning and Control

Identifiers

Local EPrints ID: 397973
URI: http://eprints.soton.ac.uk/id/eprint/397973
PURE UUID: 9cf8aeec-58c8-4820-ad90-2f2012d54a9a
ORCID for Jonathon S. Hare: ORCID iD orcid.org/0000-0003-2921-4283

Catalogue record

Date deposited: 13 Jul 2016 11:09
Last modified: 17 Jul 2017 18:34

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Contributors

Author: Nawaf Y. Almudhahka
Author: Mark S. Nixon

University divisions

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