survey

Open access

A Survey on Gait Recognition via Wearable Sensors

Authors:

Maria De Marsico,

Alessio MeccaAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 52, Issue 4

Article No.: 86, Pages 1 - 39

https://doi.org/10.1145/3340293

Published: 30 August 2019 Publication History

All formats PDF

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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Cited By

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A Survey on Gait Recognition via Wearable Sensors

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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
Department of Computer and Information Science and Engineering

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Publication History

Published: 30 August 2019

Accepted: 01 June 2019

Revised: 01 February 2019

Received: 01 June 2018

Published in CSUR Volume 52, Issue 4

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Italian Ministry of Education, University and Research
Grant PRIN 2015 COSMOS: “COntactlesS Multibiometric mObile System in the wild”

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Cited By

Munusamy VSenthilkumar S(2024)Emerging trends in gait recognition based on deep learning: a surveyPeerJ Computer Science10.7717/peerj-cs.215810(e2158)Online publication date: 10-Jul-2024
https://doi.org/10.7717/peerj-cs.2158
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