Journal Article10.4304/JCP.1.7.51-59
Biometric Gait Authentication Using Accelerometer Sensor
396
TL;DR: This paper presents a biometric user authentication based on a person’s gait patterns extracted from a physical device attached to the lower leg using histogram similarity and cycle length methods.
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Abstract: This paper presents a biometric user authentication based on a person’s gait. Unlike most previous gait recognition approaches, which are based on machine vision techniques, in our approach gait patterns are extracted from a physical device attached to the lower leg. From the output of the device accelerations in three directions: vertical, forward-backward, and sideways motion of the lower leg are obtained. A combination of these accelerations is used for authentication. Applying two different methods, histogram similarity and cycle length, equal error rates (EER) of 5% and 9% were achieved, respectively.
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References
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Jani Mäntyjärvi,M. Lindholm,Elena Vildjiounaite,Satu-Marja Mäkelä,H.A. Ailisto +4 more
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TL;DR: It was shown to be possible to identify users of portable devices from gait signals acquired with three-dimensional accelerometers with this novel gait recognition method.
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•Proceedings Article
Sheep, Goats, Lambs and Wolves: A Statistical Analysis of Speaker Performance in the NIST 1998 Speaker Recognition Evaluation
George R. Doddington,Walter Liggett,Alvin F. Martin,Mark A. Przybocki,Douglas A. Reynolds +4 more
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TL;DR: This paper proposes statistical tests for the existence of sheep, goats, lambs and wolves and applies these tests to hunt for such animals using results from the 1998 NIST speaker recognition evaluation.