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Driving Fatigue Characterization using Feature Ranking [r-libre/2864]

Henni, Khadidja; Mezghani, Neila; Gouin-Vallerand, Charles; Ruer, Perrine, & Vallières, Évelyne F. (2018). Driving Fatigue Characterization using Feature Ranking. In 9th International Symposium on Signal, Image, Video and Communications (ISIVC) (p. 209-214). IEEE. ISBN 978-1-5386-8174-9 https://doi.org/10.1109/ISIVC.2018.8709179

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Item Type: Papers in Conference Proceedings
Refereed: Yes
Status: Published
Abstract: The purpose of this study is to characterize driving fatigue using a set of facial features. These features are derived from facial expression and measure eyes and head behaviors, such as PERCLOS, blink frequency and their duration, micro-sleep, head nodding and face position. We investigated feature ranking methods to identify relevant features characterizing driving fatigue. Supervised and unsupervised classification techniques were used to evaluate the identified feature effectiveness. Experimental results are performed on a real-world database, collected through the FaceLab system from 66 senior drivers when driving an instrumented car on a highway.
Official URL: https://ieeexplore.ieee.org/abstract/document/8709...
Depositor: Ayena, Johannes
Owner / Manager: Johannes Ayena
Deposited: 31 Jan 2023 20:57
Last Modified: 31 Jan 2023 20:57

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