Abstract
Anti-spoofing has become more important in face recognition systems. This paper proposes a novel approach to resist 3D face mask attacks, which jointly uses texture and shape features. Different from existing methods where depth information by extra equipments is required, we reconstruct geometry cues from RGB images through 3D Morphable Model. The hand-crafted features as well as the deep ones are then extracted to comprehensively represent texture and shape differences between real and fake faces and finally fused for decision making. The experiments are carried out on the 3D-MAD dataset and the competitive results indicate the effectiveness.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Akshay Agarwal, Richa Singh, and Mayank Vatsa. Face anti-spoofing using haralick features. In IEEE International Conference on Biometrics Theory, Applications and Systems, pages 1–6, 2016
Angelopoulou, Elli: Understanding the color of human skin, pp. 243–251. In SPIE Human Vision and Electronic, Imaging (2001)
Yousef Atoum, Yaojie Liu, Amin Jourabloo, and Xiaoming Liu. Face anti-spoofing using patch and depth-based cnns. In IEEE International Joint Conference on Biometrics, pages 319–328, 2017
Samarth Bharadwaj, Tejas I. Dhamecha, Mayank Vatsa, and Richa Singh. Computationally efficient face spoofing detection with motion magnification. In IEEE Conference on Computer Vision and Pattern Recognition Workshops, pages 105–110, 2013
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. Imagenet: A large-scale hierarchical image database. In IEEE Conference on Computer Vision and Pattern Recognition, pages 248–255, 2009
Dowdall, Jonathan, Pavlidis, Ioannis, Bebis, George: Face detection in the near-ir spectrum. Image and Vision Computing 21(7), 565–578 (2003)
Nesli Erdogmus and Sébastien Marcel. Spoofing in 2d face recognition with 3d masks and anti-spoofing with kinect. In IEEE International Conference on Biometrics: Theory, Applications and Systems, pages 1–6, 2013
Erdogmus, Nesli, Marcel, Sébastien: Spoofing face recognition with 3d masks. IEEE Transactions on Information Forensics and Security 9(7), 1084–1097 (2014)
Galbally, Javier, Marcel, Sébastien, Fierrez, Julian: Image quality assessment for fake biometric detection: Application to iris, fingerprint, and face recognition. IEEE Transactions on Image Processing 23(2), 710–724 (2014)
Huang, Di, Ardabilian, Mohsen, Wang, Yunhong, Chen, Liming: 3-d face recognition using elbp-based facial description and local feature hybrid matching. Transactions on Information Forensics and Security 7(5), 1551–1565 (2012)
Di Huang, Karima Ouji, Mohsen Ardabilian, Yunhong Wang, and Liming Chen. 3d face recognition based on local shape patterns and sparse representation classifier. In International Conference on Multimedia Modeling, pages 206–216. Springer, 2011
Huang, Di, Shan, Caifeng, Ardabilian, Mohsen, Wang, Yunhong, Chen, Liming: Local binary patterns and its application to facial image analysis: a survey. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 41(6), 765–781 (2011)
Di Huang, Yunhong Wang, and Yiding Wang. A robust method for near infrared face recognition based on extended local binary pattern. In International Symposium on Visual Computing, pages 437–446. Springer, 2007
Patrik Huber, Guosheng Hu, Rafael Tena, Pouria Mortazavian, Willem P Koppen, William J. Christmas, Matthias Rätsch, and Josef Kittler. A multiresolution 3d morphable face model and fitting framework. In International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2016
Andrea Lagorio, Massimo Tistarelli, Marinella Cadoni, Clinton Fookes, and Sridha Sridharan. Liveness detection based on 3d face shape analysis. In IEEE International Workshop on Biometrics and Forensics, pages 1–4, 2013
Huibin Li, Di Huang, Liming Chen, Yunhong Wang, and Jean-Marie Morvan. A group of facial normal descriptors for recognizing 3d identical twins. In IEEE International Conference on Biometrics: Theory, Applications and Systems, pages 271–277. IEEE, 2012
Huibin Li, Di Huang, Jean-Marie Morvan, and Liming Chen. Learning weighted sparse representation of encoded facial normal information for expression-robust 3d face recognition. In IEEE International Joint Conference on Biometrics, pages 1–7. IEEE, 2011
Li, Huibin, Huang, Di, Morvan, Jean-Marie, Chen, Liming, Wang, Yunhong: Expression-robust 3d face recognition via weighted sparse representation of multi-scale and multi-component local normal patterns. Neurocomputing 133, 179–193 (2014)
Lei Li, Xiaoyi Feng, Zinelabidine Boulkenafet, Zhaoqiang Xia, Mingming Li, and Abdenour Hadid. An original face anti-spoofing approach using partial convolutional neural network. In IEEE International Conference on Image Processing Theory, Tools and Applications, pages 1–6, 2017
Siqi Liu, Pong C. Yuen, Shengping Zhang, and Guoying Zhao. 3d mask face anti-spoofing with remote photoplethysmography. In European Conference on Computer Vision, pages 85–100. Springer, 2016
Jukka Maatta, Abdenour Hadid, and Matti Pietikainen. Face spoofing detection from single images using micro-texture analysis. In IEEE International Joint Conference on Biometrics, pages 1–7, 2011
Ioannis Pavlidis and Peter Symosek. The imaging issue in an automatic face/disguise detection system. In IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications, pages 15–24, 2000
Tiago De Freitas Pereira, André Anjos, José Mario De Martino, and Sébastien Marcel. Lbp-top based countermeasure against face spoofing attacks. In IEEE International Conference on Computer Vision, pages 121–132, 2012
De Freitas, Tiago, Pereira, Jukka Komulainen, Anjos, André, Martino, José Mario De, Hadid, Abdenour, Pietikäinen, Matti, Marcel, Sébastien: Face liveness detection using dynamic texture. Eurasip Journal on Image and Video Processing 2014(1), 2 (2014)
P Jonathon Phillips, Patrick J Flynn, Todd Scruggs, Kevin W Bowyer, Jin Chang, Kevin Hoffman, Joe Marques, Jaesik Min, and William Worek. Overview of the face recognition grand challenge. In IEEE Conference on Computer Vision and Pattern Rrecognition, pages 947–954, 2005
Rakotomamonjy, Alain: Francis R Bach, Stéphane Canu, and Yves Grandvalet. Simplemkl. Journal of Machine Learning Research 9(3), 2491–2521 (2008)
Rui Shao, Xiangyuan Lan, and Pong C. Yuen. Deep convolutional dynamic texture learning with adaptive channel-discriminability for 3d mask face anti-spoofing. In IEEE International Joint Conference on Biometrics, pages 748–755, 2017
Karen Simonyan and Andrew Zisserman. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556, 2014
Di Wen, Hu, Han, and Anil K. Jain., : Face spoof detection with image distortion analysis. IEEE Transactions on Information Forensics and Security 10(4), 746–761 (2015)
Zhenqi Xu, Shan Li, and Weihong Deng. Learning temporal features using lstm-cnn architecture for face anti-spoofing. In IAPR Asian Conference on Pattern Recognition, pages 141–145, 2016
Acknowledgment
This work is supported by the National Natural Science Foundation of China (No. 61673033).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Wang, Y., Chen, S., Li, W., Huang, D., Wang, Y. (2018). Face Anti-spoofing to 3D Masks by Combining Texture and Geometry Features. In: Zhou, J., et al. Biometric Recognition. CCBR 2018. Lecture Notes in Computer Science(), vol 10996. Springer, Cham. https://doi.org/10.1007/978-3-319-97909-0_43
Download citation
DOI: https://doi.org/10.1007/978-3-319-97909-0_43
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-97908-3
Online ISBN: 978-3-319-97909-0
eBook Packages: Computer ScienceComputer Science (R0)