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Henni, Khadidja; Mezghani, Neila; Gouin-Vallerand, Charles; Ruer, Perrine et Vallières, Évelyne F. (2018). Driving Fatigue Characterization using Feature Ranking. Dans 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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Contenu du fichier : Version de l'éditeur Accès restreint |
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| Catégorie de document : | Communications dans des actes de congrès/colloques |
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| Évaluation par un comité de lecture : | Oui |
| Étape de publication : | Publié |
| Résumé : | 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. |
| Adresse de la version officielle : | https://ieeexplore.ieee.org/abstract/document/8709... |
| Déposant: | Ayena, Johannes |
| Responsable : | Neila Mezghani |
| Dépôt : | 31 janv. 2023 20:57 |
| Dernière modification : | 07 août 2024 15:39 |
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