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Title: Face Presentation Attack with Latex Masks in Multispectral Videos
Face recognition systems are susceptible to presentation attacks such as printed photo attacks, replay attacks, and 3D mask attacks. These attacks, primarily studied in visible spectrum, aim to obfuscate or impersonate a person’s identity. This paper presents a unique multispectral video face database for face presentation attack using latex and paper masks. The proposed Multispectral Latex Mask based Video Face Presentation Attack (MLFP) database contains 1350 videos in visible, near infrared, and thermal spectrums. Since the database consists of videos of subjects without any mask as well as wearing ten different masks, the effect of identity concealment is analyzed in each spectrum using face recognition algorithms. We also present the performance of existing presentation attack detection algorithms on the proposed MLFP database. It is observed that the thermal imaging spectrum is most effective in detecting face presentation attacks.  more » « less
Award ID(s):
1650474 1066197
NSF-PAR ID:
10053776
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshop.
Page Range / eLocation ID:
275 to 283
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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