A Low-cost Life Sign Detection Method based on Time Series Analysis of Facial Feature Points.

Publikationstyp
Konferenz
Autor(en)
Timon Bloecher, Leyre Garralda Iriarte, Johannes Schneider, Christoph Zimmermann, Wilhelm Stork:
Jahr
2017
Buchtitel
BIOSTEC BIOSIGNALS 2017
Abstract
The use of image based liveness detection 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 the complexity and the costs of the system. In this work, we propose an effective and low-cost face spoofing detector program for 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 positions, life signs have been exploited to develop a system being able to recognize false detections and anti-spoofing attacks. To verify the performance, experiments on three different benchmark datasets, namely, CASIA face anti-spoofing, MSU and IDIAP Replay-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.
Link
http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0006141601470154
DOI
10.5220/0006141601470154
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