Authors:
Timon Bloecher
1
;
Leyre Garralda Iriarte
2
;
Johannes Schneider
1
;
Christoph Zimmermann
1
and
Wilhelm Stork
1
Affiliations:
1
FZI Forschungszentrum Informatik, Germany
;
2
Public University of Navarre, Spain
Keyword(s):
Anti-spoofing, Biometrics, Presentation Attack Detection, Blinking Rate, Face Detection, Face Tracking, Face Liveness Detection, Life Signs, Time Series Analysis, Photoplethysmography Imaging (PPGI).
Abstract:
The use of image based presentation attack detection (PAD) systems has experienced an enormous growth of
interest in recent years. The most accurate techniques in literature addressing this topic rely on the verification
of the actual three-dimensionality of the face, which increases complexity and costs of the system. In this
work, we propose an effective and low-cost face spoofing detector system to supplement a PPGI-based vital
signal monitoring application. Starting from a set of automatically located facial feature points, the movement
information of this set of points was obtained. Based on a time series analysis of the landmark position
distances using peak descriptors and cross-correlation coefficients as classifiers in a sliding window, life signs
have been exploited to develop a system being able to recognize false detections and biometric spoofs. To
verify the performance, experiments on three different benchmark datasets (CASIA face anti-spoofing, MSU
and IDIAP R
eplay-Attack databases) were made. The evaluation of the proposed low-cost approach showed
good results (accuracy of ~85-95%) compared to more resource-intensive state-of-the-art methods.
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