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Real-Time Face Detection and Motion Analysis With Application in “Liveness” Assessment
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).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
2007 (English)In: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 2, no 3 part 2, 548-558 p.Article in journal (Refereed) Published
Abstract [en]

A robust face detection technique along with mouth localization, processing every frame in real time (video rate), is presented. Moreover, it is exploited for motion analysis onsite to verify "liveness" as well as to achieve lip reading of digits. A methodological novelty is the suggested quantized angle features ("quangles") being designed for illumination invariance without the need for preprocessing (e.g., histogram equalization). This is achieved by using both the gradient direction and the double angle direction (the structure tensor angle), and by ignoring the magnitude of the gradient. Boosting techniques are applied in a quantized feature space. A major benefit is reduced processing time (i.e., that the training of effective cascaded classifiers is feasible in very short time, less than 1 h for data sets of order 104). Scale invariance is implemented through the use of an image scale pyramid. We propose "liveness" verification barriers as applications for which a significant amount of computation is avoided when estimating motion. Novel strategies to avert advanced spoofing attempts (e.g., replayed videos which include person utterances) are demonstrated. We present favorable results on face detection for the YALE face test set and competitive results for the CMU-MIT frontal face test set as well as on "liveness" verification barriers.

Place, publisher, year, edition, pages
New York: IEEE Press, 2007. Vol. 2, no 3 part 2, 548-558 p.
Keyword [en]
AdaBoost, antispoofing, face detection, landmark detection, lip reading, liveness, object detection, optical flow of lines, quantized angles, real-time processing, support vector machine, SVM
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-2021DOI: 10.1109/TIFS.2007.902037ISI: 000248832500007Scopus ID: 2-s2.0-34548094310Local ID: 2082/2416OAI: oai:DiVA.org:hh-2021DiVA: diva2:239239
Note

©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Available from: 2008-10-06 Created: 2008-10-06 Last updated: 2012-12-12Bibliographically approved

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Kollreider, KlausFronthaler, HartwigFaraj, MaycelBigun, Josef
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
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  • vancouver
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More styles
Language
  • de-DE
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  • Other locale
More languages
Output format
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