@InProceedings{MohammadN.S.Jahromi2018,
author="Mohammad N. S. Jahromi
and Morten Bojesen Bonderup
and Maryam Asadi-Aghbolaghi
and Egils Avots
and Kamal Nasrollahi
and Sergio Escalera
and Shohreh Kasaei
and Thomas B. Moeslund
and Gholamreza Anbarjafari",
title="Automatic Access Control Based on Face and Hand Biometrics in a Non-cooperative Context",
booktitle="IEEE Winter Applications of Computer Vision Workshops",
year="2018",
pages="28--36",
optkeywords="IEEE Winter Applications of Computer Vision Workshops",
abstract="Automatic access control systems (ACS) based on the human biometrics or physical tokens are widely employed in public and private areas. Yet these systems, in their conventional forms, are restricted to active interaction from the users. In scenarios where users are not cooperating with the system, these systems are challenged. Failure in cooperation with the biometric systems might be intentional or because the users are incapable of handling the interaction procedure with the biometric system or simply forget to cooperate with it, due to for example, illness like dementia. This work introduces a challenging bimodal database, including face and hand information of the users when they approach a door to open it by its handle in a noncooperative context. We have defined two (an easy and a challenging) protocols on how to use the database. We have reported results on many baseline methods, including deep learning techniques as well as conventional methods on the database. The obtained results show the merit of the proposed database and the challenging nature of access control with non-cooperative users.",
optnote="HUPBA; 602.133",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3121), last updated on Mon, 25 Mar 2019 10:46:22 +0100",
doi="10.1109/WACVW.2018.00009"
}