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Non-intrusive liveness detection by face images
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).ORCID iD: 0000-0002-4929-1262
2009 (English)In: Image and Vision Computing, ISSN 0262-8856, E-ISSN 1872-8138, Vol. 27, no 3, p. 233-244Article in journal (Refereed) Published
Abstract [en]

A technique evaluating liveness in face image sequences is presented. To ensure the actual presence of a live face in contrast to a photograph (playback attack), is a significant problem in face authentication to the extent that anti-spoofing measures are highly desirable. The purpose of the proposed system is to assist in a biometric authentication framework, by adding liveness awareness in a non-intrusive manner. Analyzing the trajectories of certain parts of a live face reveals valuable information to discriminate it against a spoofed one. The proposed system uses a lightweight novel optical flow, which is especially applicable in face motion estimation based on the structure tensor and inputs of a few frames. For reliable face part detection, the system utilizes a model-based local Gabor decomposition and SVM experts, where selected points from a retinotopic grid are used to form regional face models. Also the estimated optical flow is exploited to detect a face part. The whole procedure, starting with three images as input and finishing in a liveness score, is executed in near real-time without special purpose hardware. Experimental results on the proposed system are presented on both a public database and spoofing attack simulations.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2009. Vol. 27, no 3, p. 233-244
Keywords [en]
Face liveness, Liveness detection, Anti-spoofing measures, Optical flow, Motion of lines, Optical flow of lines, Orientation estimation, Face part models, Retinotopic vision, Local Gabor decomposition, Support vector machine classification
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-2180DOI: 10.1016/j.imavis.2007.05.004ISI: 000262386600003Scopus ID: 2-s2.0-56349109534Local ID: 2082/2577OAI: oai:DiVA.org:hh-2180DiVA, id: diva2:239398
Available from: 2008-12-04 Created: 2008-12-04 Last updated: 2018-03-23Bibliographically approved

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Kollreider, KlausFronthaler, HartwigBigun, Josef

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