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A joint density based rank-score fusion for soft biometric recognition at a distance

A joint density based rank-score fusion for soft biometric recognition at a distance
A joint density based rank-score fusion for soft biometric recognition at a distance
In order to improve recognition performance, fusion has become a key technique in the recent years. Compared with single-mode biometrics, the recognition rate of multi-modal biometric systems is improved and the final decision is more confident. This paper introduces a novel joint density distribution based rank-score fusion strategy that combines rank and score information. Recognition at a distance has only recently been of interest in soft biometrics. We create a new soft biometric database containing the human face, body and clothing attributes at three different distances to investigate the influence by distance on soft biometric fusion. A comparative study about our method and other state of the art rank level and score level fusion methods are also conducted in this paper. The experiments are performed using a soft biometric database we created. The results demonstrate the recognition performance is significantly improved by our proposed method.
Guo, Bingchen
6e425926-551d-40c2-9c12-e2509d76baa2
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carter, John
e05be2f9-991d-4476-bb50-ae91606389da
Guo, Bingchen
6e425926-551d-40c2-9c12-e2509d76baa2
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carter, John
e05be2f9-991d-4476-bb50-ae91606389da

Guo, Bingchen, Nixon, Mark and Carter, John (2018) A joint density based rank-score fusion for soft biometric recognition at a distance. At ICPR 2018: International Conference on Pattern Recognition 2018 (24/08/18) ICPR 2018: International Conference on Pattern Recognition 2018, Beijing, China. 20 - 24 Aug 2018. 6 pp.

Record type: Conference or Workshop Item (Paper)

Abstract

In order to improve recognition performance, fusion has become a key technique in the recent years. Compared with single-mode biometrics, the recognition rate of multi-modal biometric systems is improved and the final decision is more confident. This paper introduces a novel joint density distribution based rank-score fusion strategy that combines rank and score information. Recognition at a distance has only recently been of interest in soft biometrics. We create a new soft biometric database containing the human face, body and clothing attributes at three different distances to investigate the influence by distance on soft biometric fusion. A comparative study about our method and other state of the art rank level and score level fusion methods are also conducted in this paper. The experiments are performed using a soft biometric database we created. The results demonstrate the recognition performance is significantly improved by our proposed method.

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Accepted/In Press date: 2018
Published date: August 2018
Venue - Dates: ICPR 2018: International Conference on Pattern Recognition 2018, Beijing, China, 2018-08-20 - 2018-08-24

Identifiers

Local EPrints ID: 419825
URI: https://eprints.soton.ac.uk/id/eprint/419825
PURE UUID: f418d3e8-773c-4a70-989c-cfc54c642ccc
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 23 Apr 2018 16:30
Last modified: 02 Aug 2018 00:35

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Contributors

Author: Bingchen Guo
Author: Mark Nixon ORCID iD
Author: John Carter

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