Robust User Identification Based on Facial Action Units Unaffected by Users' Emotions

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dc.contributor.author Buettner, Ricardo
dc.date.accessioned 2017-12-28T00:34:20Z
dc.date.available 2017-12-28T00:34:20Z
dc.date.issued 2018-01-03
dc.description.abstract We report on promising results concerning the identification of a user just based on its facial action units. The related Random Forests classifier which analyzed facial action unit activity captured by an ordinary webcam achieved very good values for accuracy (97.24 percent) and specificity (99.92 percent). In combination with a PIN request the degree of specificity raised to over 99.999 percent. The proposed biometrical method is unaffected by a user's emotions, easy to use, cost efficient, non-invasive, and contact-free and can be used in human-machine interaction as well as in secure access control systems.
dc.format.extent 9 pages
dc.identifier.doi 10.24251/HICSS.2018.036
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/49923
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Human-Computer Interaction: Informing Design Utilizing Behavioral, Neurophysiological, and Design Science Methods
dc.subject biometric authentication, facial action analysis, human computer interaction, machine learning, Random Forests
dc.title Robust User Identification Based on Facial Action Units Unaffected by Users' Emotions
dc.type Conference Paper
dc.type.dcmi Text
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