Title

Liveness Measurements Using Optical Flow for Biometric Person Authentication

Journal title

Metrology and Measurement Systems

Yearbook

2012

Issue

No 2

Authors

Smiatacz, Maciej

Keywords

liveness detection ; biometrics ; optical flow ; face recognition

Divisions of PAS

Nauki Techniczne

Coverage

257-268

Publisher

Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation

Date

2012

Type

Artykuły / Articles

Identifier

DOI: 10.2478/v10178-012-0022-y ; ISSN 2080-9050, e-ISSN 2300-1941

Source

Metrology and Measurement Systems; 2012; No 2; 257-268

References

Researchers spoof, bypass face-recognition authentication systems, <i>Homeland Security NewsWire</i> (2009). <a target="_blank" href='http://www.homelandsecuritynewswire.com/researchers-spoof-bypass-face-recognition-authentication-systems'>http://www.homelandsecuritynewswire.com/researchers-spoof-bypass-face-recognition-authentication-systems</a> ; SART-2, Biometric security system for mobile workstations (2012). <a target="_blank" href='http://sart2.eti.pg.gda.pl/en/'>http://sart2.eti.pg.gda.pl/en/</a> ; Jee H. (2006), Liveness Detection for Embedded Face Recognition System, International Journal of Biomedical Sciences, 235. ; Viola P. (2004), Robust Real-Time Face Detection, Int. J. Comp. Vision, 57, 2, 137, doi.org/10.1023/B:VISI.0000013087.49260.fb ; Wang H. (2004), Face Recognition under Varying Lighting Conditions Using Self Quotient Image, null. ; Pan G. (2007), Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera, null. ; Huang C.-H. (2008), SVM-based One-Against-Many Algorithm for Liveness Face Authentication, null, 744. ; Bao W. (2009), A Liveness Detection Method for Face Recognition Based on Optical Flow Field, null, 233. ; Dembski J. (2010), Advances in Systems Science, 353. ; Horn B. (1981), Determining Optical Flow, Artificial Intelligence, 17, 185, doi.org/10.1016/0004-3702(81)90024-2 ; Farnebäck G. (2000), Fast and Accurate Motion Estimation using Orientation Tensors and Parametric Motion Models, null. ; Farnebäck, G. (1999). Spatial Domain Methods for Orientation and Velocity Estimation. <i>Lic. Thesis LiU-Tek-Lic-1999:13.</i> Dept. EE, Linköping University. ; Burges Ch. (1998), A Tutorial on Support Vector Machines for Pattern Recognition, Data Mining and Knowledge Discovery, 2, 2, 121, doi.org/10.1023/A:1009715923555 ; Cui J. (2011), Analog circuit fault classification using improved one-against-one Support Vector Machines, Metrol. Meas. Sys, 18, 4, 569, doi.org/10.2478/v10178-011-0055-7 ; Smiatacz M. (2011), SDF classifier revisited, Expert Systems, doi.org/10.1111/j.1468-0394.2011.00589.x ; Beauty check, Average faces (2012). <a target="_blank" href='http://www.uni-regensburg.de/Fakultaeten/phil_Fak_II/Psychologie/Psy_II/beautycheck/english/durchschnittsgesichter/durchschnittsgesichter.htm'>http://www.uni-regensburg.de/Fakultaeten/phil_Fak_II/Psychologie/Psy_II/beautycheck/english/durchschnittsgesichter/durchschnittsgesichter.htm</a> ; Smiatacz M. (2010), AAM Toolkit: a system for visual object appearance modelling, Advances in Multimedia and Network Information System Technologies, Advances in Intelligent and Soft Computing, 80, 121.