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On the assessment of face image quality based on handcrafted features

 
: Henniger, Olaf; Fu, Biying; Chen, Cong

:
Volltext urn:nbn:de:0011-n-6030788 (713 KByte PDF)
MD5 Fingerprint: bb7500565268577e2d904f076fe14a9f
Erstellt am: 6.10.2020


Brömme, Arslan (Ed.) ; Gesellschaft für Informatik -GI-, Bonn:
BIOSIG 2020, 19th International Conference of the Biometrics Special Interest Group. Proceedings : 16.-18.09.2020, Fully Virtual Conference
Bonn: GI, 2020 (GI-Edition - Lecture Notes in Informatics (LNI). Proceedings P-306)
ISBN: 978-3-88579-700-5
S.273-280
Gesellschaft für Informatik, Special Interest Group on Biometrics and Electronic Signatures (BIOSIG International Conference) <19, 2020, Online>
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
ATHENE
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IGD ()
Lead Topic: Smart City; Research Line: Human computer interaction (HCI); biometrics; Biometric features; biometric standard; face recognition; image quality; CRISP; ATHENE

Abstract
This paper studies the assessment of the quality of face images, predicting the utility of face images for automated recognition. The utility of frontal face images from a publicly available dataset was assessed by comparing them with each other using commercial off-the-shelf face recognition systems. Multiple face image features delineating face symmetry and characteristics of the capture process were analysed to find features predictive of utility. The selected features were used to build system-specific and generic random forest classifiers.

: http://publica.fraunhofer.de/dokumente/N-603078.html