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

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Title:Robust User Identification Based on Facial Action Units Unaffected by Users' Emotions
Authors:Buettner, Ricardo
Keywords:Human-Computer Interaction: Informing Design Utilizing Behavioral, Neurophysiological, and Design Science Methods
biometric authentication, facial action analysis, human computer interaction, machine learning, Random Forests
Date Issued:03 Jan 2018
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.
Pages/Duration:9 pages
URI:http://hdl.handle.net/10125/49923
ISBN:978-0-9981331-1-9
DOI:10.24251/HICSS.2018.036
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Human-Computer Interaction: Informing Design Utilizing Behavioral, Neurophysiological, and Design Science Methods


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