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A Survey on Gait Recognition via Wearable Sensors

Published:30 August 2019Publication History
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Abstract

Gait is a biometric trait that can allow user authentication, though it is classified as a “soft” one due to a certain lack in permanence and to sensibility to specific conditions. The earliest research relies on computer vision, especially applied in video surveillance. More recently, the spread of wearable sensors, especially those embedded in mobile devices, has spurred a different research line. In fact, they are able to capture the dynamics of the walking pattern through simpler one-dimensional signals. This capture modality can avoid some problems related to computer vision-based techniques but suffers from specific limitations. Related research is still in a less advanced phase with respect to other biometric traits. However, many factors - the promising results achieved so far, the increasing accuracy of sensors, the ubiquitous presence of mobile devices, and the low cost of related techniques - contribute to making this biometrics attractive and suggest continuing investigating. This survey provides interested readers with a reasoned and systematic overview of problems, approaches, and available benchmarks.

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                cover image ACM Computing Surveys
                ACM Computing Surveys  Volume 52, Issue 4
                July 2020
                769 pages
                ISSN:0360-0300
                EISSN:1557-7341
                DOI:10.1145/3359984
                • Editor:
                • Sartaj Sahni
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                Publication History

                • Published: 30 August 2019
                • Accepted: 1 June 2019
                • Revised: 1 February 2019
                • Received: 1 June 2018
                Published in csur Volume 52, Issue 4

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