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Face profile biometric enhanced by eyewitness testimonies

Face profile biometric enhanced by eyewitness testimonies
Face profile biometric enhanced by eyewitness testimonies
Continuous development in surveillance systems is increasingly motivating research in biometrics to articulate unconstrained recognition of human faces. Comparative soft biometric has recently been employed to characterize eyewitness testimonies for use in a biometric system to improve the recognition accuracies of the traditional biometric systems. In this paper, we present a face profile recognition system by fusing features extracted in a traditional face recognition system and eyewitness testimonies processed in a soft biometric system to improve recognition accuracies. Here we have also demonstrated an association between our traditional face profile biometric system and the soft biometric system by numerically mapping the features extracted from a face profile to its soft biometric attributes. Our experiments on 230 subjects in XM2VTSDBdataset demonstrate 84% accuracy for traditional biometrics. The recognition rate is further improved to 98% accuracy when soft and traditional biometrics are fused.
Face profile recognition, soft biometric, Face Recognition
1
Alamri, Malak
6e6c6422-14b2-4aa8-9936-070face0f285
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Alamri, Malak
6e6c6422-14b2-4aa8-9936-070face0f285
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf

Alamri, Malak and Mahmoodi, Sasan (2022) Face profile biometric enhanced by eyewitness testimonies. 26th International Conference on Pattern Recognition, Quebec, Montreal, Canada. 21 - 25 Aug 2022. p. 1 .

Record type: Conference or Workshop Item (Paper)

Abstract

Continuous development in surveillance systems is increasingly motivating research in biometrics to articulate unconstrained recognition of human faces. Comparative soft biometric has recently been employed to characterize eyewitness testimonies for use in a biometric system to improve the recognition accuracies of the traditional biometric systems. In this paper, we present a face profile recognition system by fusing features extracted in a traditional face recognition system and eyewitness testimonies processed in a soft biometric system to improve recognition accuracies. Here we have also demonstrated an association between our traditional face profile biometric system and the soft biometric system by numerically mapping the features extracted from a face profile to its soft biometric attributes. Our experiments on 230 subjects in XM2VTSDBdataset demonstrate 84% accuracy for traditional biometrics. The recognition rate is further improved to 98% accuracy when soft and traditional biometrics are fused.

Text
ICPR2022 - Accepted Manuscript
Restricted to Repository staff only until 5 September 2022.
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More information

Published date: 21 August 2022
Venue - Dates: 26th International Conference on Pattern Recognition, Quebec, Montreal, Canada, 2022-08-21 - 2022-08-25
Keywords: Face profile recognition, soft biometric, Face Recognition

Identifiers

Local EPrints ID: 457916
URI: http://eprints.soton.ac.uk/id/eprint/457916
PURE UUID: 5a45edba-e4c9-4187-a2dc-3f7d2227ce8b

Catalogue record

Date deposited: 22 Jun 2022 16:37
Last modified: 22 Jun 2022 16:38

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Contributors

Author: Malak Alamri
Author: Sasan Mahmoodi

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