Besides revealing useful information, like gender, age, existing impairments, the gait of every person is acknowledged to be so distinctive to allow the personal identification and it is regarded as a valid biometric authentication, similarly to fingerprinting and face recognition. Although the first analyses on the gait were conducted in laboratories with dedicated equipment, portable sensors have been exploited as they become available thanks to the technology miniaturization. Aiming at an even more unobtrusive analysis, recent proposals rely on the data acquired from the 3-axis accelerometer embedded in most of the smartphones commercially available on the market. Nevertheless the analysis must be tailored to the lower-grade accelerometer and the limited computational capability of the smartphone. This paper identifies the guidelines that the state-of-the-art research proposes for the gait recognition through a smartphone and discusses the procedures that are found as more appropriate.

On gait recognition with smartphone accelerometer / Ferrero, Renato; Gandino, Filippo; Montrucchio, Bartolomeo; Rebaudengo, Maurizio; Velasco, ALEJANDRO DAVID; Benkhelifa, I.. - ELETTRONICO. - (2015), pp. 368-373. (Intervento presentato al convegno 2015 4th Mediterranean Conference on Embedded Computing (MECO) tenutosi a Budva (Montenegro) nel 14-18 Giugno 2015) [10.1109/MECO.2015.7181946].

On gait recognition with smartphone accelerometer

FERRERO, RENATO;GANDINO, FILIPPO;MONTRUCCHIO, BARTOLOMEO;REBAUDENGO, Maurizio;VELASCO, ALEJANDRO DAVID;
2015

Abstract

Besides revealing useful information, like gender, age, existing impairments, the gait of every person is acknowledged to be so distinctive to allow the personal identification and it is regarded as a valid biometric authentication, similarly to fingerprinting and face recognition. Although the first analyses on the gait were conducted in laboratories with dedicated equipment, portable sensors have been exploited as they become available thanks to the technology miniaturization. Aiming at an even more unobtrusive analysis, recent proposals rely on the data acquired from the 3-axis accelerometer embedded in most of the smartphones commercially available on the market. Nevertheless the analysis must be tailored to the lower-grade accelerometer and the limited computational capability of the smartphone. This paper identifies the guidelines that the state-of-the-art research proposes for the gait recognition through a smartphone and discusses the procedures that are found as more appropriate.
2015
978-1-4799-8999-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2609367
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