Location
Hilton Waikoloa Village, Hawaii
Event Website
http://hicss.hawaii.edu/
Start Date
1-3-2018
End Date
1-6-2018
Description
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.
Robust User Identification Based on Facial Action Units Unaffected by Users' Emotions
Hilton Waikoloa Village, Hawaii
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.
https://aisel.aisnet.org/hicss-51/cl/hci/6