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Making the Case for Safety of Machine Learning in Highly Automated Driving Read chapter Read first chapter

2017 | Supplement | Chapter

Try Walking in My Shoes, if You Can: Accurate Gait Recognition Through Deep Learning

Authors : Giacomo Giorgi, Fabio Martinelli, Andrea Saracino, Mina Sheikhalishahi

Published in: Computer Safety, Reliability, and Security

Publisher: Springer International Publishing

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Abstract

Human gait seamless continuous authentication, based on wearable accelerometers, is a novel biometric instrument which can be exploited to identify the user of mobile and wearable devices. In this paper, we present a study on recognition of user identity, by analysis of gait data, collected through body inertial sensors from 175 different users. The mechanism used for identity recognition is based on deep learning machinery, specifically on a convolutional network, trained with readings from different sensors, and on filtering and buffering mechanism to increase the accuracy. Results show a very high accuracy in both recognizing known and unknown identities.

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Metadata
Title
Try Walking in My Shoes, if You Can: Accurate Gait Recognition Through Deep Learning
Authors
Giacomo Giorgi
Fabio Martinelli
Andrea Saracino
Mina Sheikhalishahi
Copyright Year
2017
Book
Computer Safety, Reliability, and Security

Print ISBN: 978-3-319-66283-1

Electronic ISBN: 978-3-319-66284-8

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-66284-8_32

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