Smartphones are arguably candidates to become the platform of choice for ubiquitous biometric-based identity verification, thanks to their embedded sensors, reasonably good computing power and widespread diffusion. While applications of the most established biometrics like face, fingerprint and even iris have already been proposed on mobile devices, other less exploited identifiers could also be worth investigating. To this regard, a novel multi-modal approach to person authentication based on ear biometrics and gesture analysis is proposed in this paper. The idea is to coupling the discriminant power of ear, captured during the act of responding to a phone call, with the user's arm dynamics affecting the smartphone motion pattern due to behavioral and anatomical characteristics involved in this gesture. According to experiments conducted on a specifically built multi-modal database comprising a hundred subjects, we confirm that the 'responding gesture' has significant discriminating power and combined to ear features provides even greater robustness and accuracy in mobile authentication scenarios.

Smartphone enabled person authentication based on ear biometrics and arm gesture

Ricciardi, Stefano
2017-01-01

Abstract

Smartphones are arguably candidates to become the platform of choice for ubiquitous biometric-based identity verification, thanks to their embedded sensors, reasonably good computing power and widespread diffusion. While applications of the most established biometrics like face, fingerprint and even iris have already been proposed on mobile devices, other less exploited identifiers could also be worth investigating. To this regard, a novel multi-modal approach to person authentication based on ear biometrics and gesture analysis is proposed in this paper. The idea is to coupling the discriminant power of ear, captured during the act of responding to a phone call, with the user's arm dynamics affecting the smartphone motion pattern due to behavioral and anatomical characteristics involved in this gesture. According to experiments conducted on a specifically built multi-modal database comprising a hundred subjects, we confirm that the 'responding gesture' has significant discriminating power and combined to ear features provides even greater robustness and accuracy in mobile authentication scenarios.
2017
9781509018970
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/72094
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