Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/49923

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

File SizeFormat 
paper0036.pdf697.24 kBAdobe PDFView/Open

Item Summary

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
Issue Date: 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/DOI: http://hdl.handle.net/10125/49923
ISBN: 978-0-9981331-1-9
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Human-Computer Interaction: Informing Design Utilizing Behavioral, Neurophysiological, and Design Science Methods


Please contact sspace@hawaii.edu if you need this content in an alternative format.

Items in ScholarSpace are protected by copyright, with all rights reserved, unless otherwise indicated.