Damer, Naser ; Boutros, Fadi ; Süßmilch, Marius ; Kirchbuchner, Florian ; Kuijper, Arjan (2021)
Extended evaluation of the effect of real and simulated masks on face recognition performance.
In: IET Biometrics, (Early View)
doi: 10.1049/bme2.12044
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Face recognition is an essential technology in our daily lives as a contactless and convenient method of accurate identity verification. Processes such as secure login to electronic devices or identity verification at automatic border control gates are increasingly dependent on such technologies. The recent COVID‐19 pandemic has increased the focus on hygienic and contactless identity verification methods. The pandemic has led to the wide use of face masks, essential to keep the pandemic under control. The effect of mask‐wearing on face recognition in a collaborative environment is currently a sensitive yet understudied issue. Recent reports have tackled this by using face images with synthetic mask‐like face occlusions without exclusively assessing how representative they are of real face masks. These issues are addressed by presenting a specifically collected database containing three sessions, each with three different capture instructions, to simulate real use cases. The data are augmented to include previously used synthetic mask occlusions. Further studied is the effect of masked face probes on the behaviour of four face recognition systems—three academic and one commercial. This study evaluates both masked‐to‐non‐masked and masked‐to‐masked face comparisons. In addition, real masks in the database are compared with simulated masks to determine their comparative effects on face recognition performance.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2021 |
| Autor(en): | Damer, Naser ; Boutros, Fadi ; Süßmilch, Marius ; Kirchbuchner, Florian ; Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | Extended evaluation of the effect of real and simulated masks on face recognition performance |
| Sprache: | Englisch |
| Publikationsjahr: | 28 Mai 2021 |
| Verlag: | Wiley & Sons Ltd. |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IET Biometrics |
| (Heft-)Nummer: | Early View |
| DOI: | 10.1049/bme2.12044 |
| Kurzbeschreibung (Abstract): | Face recognition is an essential technology in our daily lives as a contactless and convenient method of accurate identity verification. Processes such as secure login to electronic devices or identity verification at automatic border control gates are increasingly dependent on such technologies. The recent COVID‐19 pandemic has increased the focus on hygienic and contactless identity verification methods. The pandemic has led to the wide use of face masks, essential to keep the pandemic under control. The effect of mask‐wearing on face recognition in a collaborative environment is currently a sensitive yet understudied issue. Recent reports have tackled this by using face images with synthetic mask‐like face occlusions without exclusively assessing how representative they are of real face masks. These issues are addressed by presenting a specifically collected database containing three sessions, each with three different capture instructions, to simulate real use cases. The data are augmented to include previously used synthetic mask occlusions. Further studied is the effect of masked face probes on the behaviour of four face recognition systems—three academic and one commercial. This study evaluates both masked‐to‐non‐masked and masked‐to‐masked face comparisons. In addition, real masks in the database are compared with simulated masks to determine their comparative effects on face recognition performance. |
| Freie Schlagworte: | Biometrics, Face recognition, Performance evaluation, Corona, Deep learning |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 15 Jun 2021 06:00 |
| Letzte Änderung: | 15 Jun 2021 06:00 |
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