Automatic Access Control Based on Face and Hand Biometrics in A Non-Cooperative Context

Mohammad Naser Sabet Jahromi; Morten Bojesen Bonderup; Maryam  Asadi-Aghbolaghi; Egils  Avots; Kamal Nasrollahi; Sergio Escalera Guerrero; Shohreh  Kasaei; Thomas B. Moeslund; Gholamreza  Anbarjafari

doi:10.1109/WACVW.2018.00009

Automatic Access Control Based on Face and Hand Biometrics in A Non-Cooperative Context

Mohammad Naser Sabet Jahromi, Morten Bojesen Bonderup, Maryam Asadi-Aghbolaghi, Egils Avots, Kamal Nasrollahi, Sergio Escalera Guerrero, Shohreh Kasaei, Thomas B. Moeslund, Gholamreza Anbarjafari

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

5 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2018 : Cross-Domain Biometric Recognition Workshop
Number of pages	9
Publisher	IEEE (Institute of Electrical and Electronics Engineers)
Publication date	24 Apr 2018
Pages	28-36
ISBN (Electronic)	9781538651889
DOIs	https://doi.org/10.1109/WACVW.2018.00009
Publication status	Published - 24 Apr 2018
Event	2018 IEEE Winter Applications of Computer Vision Workshops (WACVW) - Lake Tahoe, United States Duration: 15 Mar 2018 → 15 Mar 2018

Conference

Conference	2018 IEEE Winter Applications of Computer Vision Workshops (WACVW)
Country/Territory	United States
City	Lake Tahoe
Period	15/03/2018 → 15/03/2018

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Jahromi, M. N. S., Bonderup, M. B., Asadi-Aghbolaghi, M., Avots, E., Nasrollahi, K., Guerrero, S. E., Kasaei, S., Moeslund, T. B., & Anbarjafari, G. (2018). Automatic Access Control Based on Face and Hand Biometrics in A Non-Cooperative Context. In Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2018: Cross-Domain Biometric Recognition Workshop (pp. 28-36). IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/WACVW.2018.00009

Jahromi, Mohammad Naser Sabet ; Bonderup, Morten Bojesen ; Asadi-Aghbolaghi, Maryam et al. / Automatic Access Control Based on Face and Hand Biometrics in A Non-Cooperative Context. Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2018: Cross-Domain Biometric Recognition Workshop. IEEE (Institute of Electrical and Electronics Engineers), 2018. pp. 28-36

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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 theusers. 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 interactionprocedure 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.",

author = "Jahromi, {Mohammad Naser Sabet} and Bonderup, {Morten Bojesen} and Maryam Asadi-Aghbolaghi and Egils Avots and Kamal Nasrollahi and Guerrero, {Sergio Escalera} and Shohreh Kasaei and Moeslund, {Thomas B.} and Gholamreza Anbarjafari",

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Jahromi, MNS, Bonderup, MB, Asadi-Aghbolaghi, M, Avots, E, Nasrollahi, K , Guerrero, SE, Kasaei, S, Moeslund, TB & Anbarjafari, G 2018, Automatic Access Control Based on Face and Hand Biometrics in A Non-Cooperative Context. in Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2018: Cross-Domain Biometric Recognition Workshop. IEEE (Institute of Electrical and Electronics Engineers), pp. 28-36, 2018 IEEE Winter Applications of Computer Vision Workshops (WACVW), Lake Tahoe, United States, 15/03/2018. https://doi.org/10.1109/WACVW.2018.00009

Automatic Access Control Based on Face and Hand Biometrics in A Non-Cooperative Context. / Jahromi, Mohammad Naser Sabet; Bonderup, Morten Bojesen; Asadi-Aghbolaghi, Maryam et al.
Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2018: Cross-Domain Biometric Recognition Workshop. IEEE (Institute of Electrical and Electronics Engineers), 2018. p. 28-36.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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AU - Jahromi, Mohammad Naser Sabet

AU - Bonderup, Morten Bojesen

AU - Asadi-Aghbolaghi, Maryam

AU - Avots, Egils

AU - Nasrollahi, Kamal

AU - Guerrero, Sergio Escalera

AU - Kasaei, Shohreh

AU - Moeslund, Thomas B.

AU - Anbarjafari, Gholamreza

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N2 - 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 theusers. 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 interactionprocedure 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.

AB - 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 theusers. 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 interactionprocedure 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.

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BT - Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2018

PB - IEEE (Institute of Electrical and Electronics Engineers)

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ER -

Jahromi MNS, Bonderup MB, Asadi-Aghbolaghi M, Avots E, Nasrollahi K , Guerrero SE et al. Automatic Access Control Based on Face and Hand Biometrics in A Non-Cooperative Context. In Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2018: Cross-Domain Biometric Recognition Workshop. IEEE (Institute of Electrical and Electronics Engineers). 2018. p. 28-36 doi: 10.1109/WACVW.2018.00009

Automatic Access Control Based on Face and Hand Biometrics in A Non-Cooperative Context

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