Spoofing faces using makeup: An investigative study

Makeup can be used to alter the facial appearance of a person. Previous studies have established the potential of using makeup to obfuscate the identity of an individual with respect to an automated face matcher. In this work, we analyze the potential of using makeup for spoofing an identity, where an individual attempts to impersonate another person's facial appearance. In this regard, we first assemble a set of face images downloaded from the internet where individuals use facial cosmetics to impersonate celebrities. We next determine the impact of this alteration on two different face matchers. Experiments suggest that automated face matchers are vulnerable to makeup-induced spoofing and that the success of spoofing is impacted by the appearance of the impersonator's face and the target face being spoofed. Further, an identification experiment is conducted to show that the spoofed faces are successfully matched at better ranks after the application of makeup. To the best of our knowledge, this is the first work that systematically studies the impact of makeup-induced face spoofing on automated face recognition.

[1]  Arun Ross,et al.  An ensemble of patch-based subspaces for makeup-robust face recognition , 2016, Inf. Fusion.

[2]  A. Dantcheva Female facial aesthetics based on soft biometrics and photo-quality , 2011 .

[3]  Jean-Luc Dugelay,et al.  Facial cosmetics database and impact analysis on automatic face recognition , 2013, 2013 IEEE 15th International Workshop on Multimedia Signal Processing (MMSP).

[4]  Jean-Luc Dugelay,et al.  Facial makeup detection technique based on texture and shape analysis , 2015, 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).

[5]  Yi Li,et al.  Face Liveness Detection from a Single Image with Sparse Low Rank Bilinear Discriminative Model , 2010, ECCV.

[6]  Arun Ross,et al.  An introduction to biometrics , 2008, ICPR 2008.

[7]  Shengcai Liao,et al.  A benchmark study of large-scale unconstrained face recognition , 2014, IEEE International Joint Conference on Biometrics.

[8]  Tieniu Tan,et al.  Counterfeit iris detection based on texture analysis , 2008, 2008 19th International Conference on Pattern Recognition.

[9]  Andrew Zisserman,et al.  Deep Face Recognition , 2015, BMVC.

[10]  Arun Ross,et al.  Impact of facial cosmetics on automatic gender and age estimation algorithms , 2014, 2014 International Conference on Computer Vision Theory and Applications (VISAPP).

[11]  Anil K. Jain,et al.  Secure Face Unlock: Spoof Detection on Smartphones , 2016, IEEE Transactions on Information Forensics and Security.

[12]  Jean-Luc Dugelay,et al.  Countermeasure for the protection of face recognition systems against mask attacks , 2013, 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).

[13]  Tieniu Tan,et al.  Live face detection based on the analysis of Fourier spectra , 2004, SPIE Defense + Commercial Sensing.

[14]  Shuicheng Yan,et al.  Face Authentication With Makeup Changes , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[15]  Brian J F Wong,et al.  Medical Makeup for Concealing Facial Scars , 2012, Facial Plastic Surgery.

[16]  Arun Ross,et al.  Automatic facial makeup detection with application in face recognition , 2013, 2013 International Conference on Biometrics (ICB).

[17]  Arun Ross,et al.  Can facial cosmetics affect the matching accuracy of face recognition systems? , 2012, 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[18]  Lin Sun,et al.  Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[19]  Matti Pietikäinen,et al.  Face spoofing detection from single images using texture and local shape analysis , 2012, IET Biom..

[20]  Nathan J. Short,et al.  Effects of surface materials on polarimetric-thermal measurements: applications to face recognition. , 2016, Applied optics.

[21]  Sébastien Marcel,et al.  Counter-measures to photo attacks in face recognition: A public database and a baseline , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[22]  Marwan Mattar,et al.  Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments , 2008 .

[23]  Matti Pietikäinen,et al.  Competition on counter measures to 2-D facial spoofing attacks , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[24]  Anil K. Jain,et al.  Altered Fingerprints: Analysis and Detection , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.