Abstract
In this paper we study face Presentation Attack Detection (PAD) against realistic 3D mask and high quality photo attacks in dynamic scenarios. We perform a comparison between a new pulse-based PAD approach based on a combination of a skin detector and a chrominance method, and the system used in our previous works (based on Blind Source Separation techniques, BSS). We also propose and study heuristical and statistical approaches for performing continuous PAD with low latency and false non-match rate. Results are reported using the 3D Mask Attack Database (3DMAD), and a self-collected dataset called BiDA Heart Rate Database (BiDA HR) including different video durations, resolutions, frame rates and attack artifacts. Several conclusions can be drawn from this work: (1) chrominance and BSS methods perform similarly under the controlled and favorable conditions found in 3DMAD and BiDA HR, (2) combining pulse information extracted from short-time sequences (e.g. 3 s) can be discriminant enough for performing the PAD task, (3) a high increase in PAD performance can be achieved with simple PAD score combination, and (4) the statistical method for continuous PAD outperforms the simple PAD score combination but it needs more data for building the statistical models.
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
Notes
- 1.
As error measures we have mentioned IAPMR and FNMR as defined and discussed by Galbally et al. [9]. Modifying the Decision Threshold until those error rates are equal we obtain the Presentation Attack Equal Error Rate, PAEER, defined and discussed in [9]. Here we follow [9] using PAEER to evaluate the presentation attacks, but calling it as EER for simplicity.
References
Allen, J.: Photoplethysmography and its application in clinical physiological measurement. Physiol. Measur. 28(3), R1–R39 (2007)
Alonso-Fernandez, F., Fierrez, J., Ortega-Garcia, J.: Quality measures in biometric systems. IEEE Secur. Priv. 10(6), 52–62 (2012)
Bharadwaj, S., Dhamecha, T.I., Vatsa, M., Singh, R.: Computationally efficient face spoofing detection with motion magnification. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 105–110 (2013)
Dargie, W.: Analysis of time and frequency domain features of accelerometer measurements. In: International Conference on Computer Communication and Networks. IEEE (2009)
De Haan, G., Jeanne, V.: Robust pulse rate from chrominance-based rPPG. IEEE Trans. Biomed. Eng. 60(10), 2878–2886 (2013)
Erdogmus, N., Marcel, S.: Spoofing face recognition with 3D masks. IEEE Trans. Inf. Forensics Secur. 9(7), 1084–1097 (2014)
Fierrez, J., Pozo, A., Martinez-Diaz, M., Galbally, J., Morales, A.: Benchmarking touchscreen biometrics for mobile authentication. IEEE Trans. Inf. Forensics Secur. 13(11), 2720–2733 (2018)
Fierrez, J., Morales, A., Vera-Rodriguez, R., Camacho, D.: Multiple classifiers in biometrics. Part 2: trends and challenges. Inf. Fusion 44, 103–112 (2018)
Galbally, J., Gomez-Barrero, M., Ross, A.: Accuracy evaluation of handwritten signature verification: rethinking the random-skilled forgeries dichotomy. In: IEEE International Joint Conference on Biometrics (IJCB), pp. 302–310 (2017)
Hadid, A., Evans, N., Marcel, S., Fierrez, J.: Biometrics systems under spoofing attack: an evaluation methodology and lessons learned. IEEE Sig. Process. Mag. 32(5), 20–30 (2015)
Hernandez-Ortega, J., Fierrez, J., Morales, A., Tome, P.: Time analysis of pulse-based face anti-spoofing in visible and NIR. In: IEEE CVPR Computer Society Workshop on Biometrics (2018)
Li, X., Komulainen, J., Zhao, G., Yuen, P.C., Pietikäinen, M.: Generalized face anti-spoofing by detecting pulse from face videos. In: International Conference on Pattern Recognition (ICPR), pp. 4244–4249. IEEE (2016)
Mahmoud, T.M., et al.: A new fast skin color detection technique. World Acad. Sci. Eng. Technol. 43, 501–505 (2008)
Marcel, S., Nixon, M.S., Fierrez, J., Evans, N.: Handbook of Biometric Anti-Spoofing, 2nd edn. Springer, Heidelberg (2019)
McDuff, D., Gontarek, S., Picard, R.W.: Improvements in remote cardiopulmonary measurement using a five band digital camera. IEEE Trans. Biomed. Eng. 61(10), 2593–2601 (2014)
Perera, P., Patel, V.M.: Efficient and low latency detection of intruders in mobile active authentication. IEEE Trans. Inf. Forensics Secur. 13(6), 1392–1405 (2018)
Poh, M.Z., McDuff, D.J., Picard, R.W.: Advancements in noncontact, multiparameter physiological measurements using a webcam. IEEE Trans. Biomed. Eng. 58(1), 7–11 (2011)
Rapczynski, M., Werner, P., Al-Hamadi, A.: Continuous low latency heart rate estimation from painful faces in real time. In: International Conference on Pattern Recognition (ICPR), pp. 1165–1170 (2016)
Tasli, H.E., Gudi, A., den Uyl, M.: Remote PPG based vital sign measurement using adaptive facial regions. In: Proceedings of IEEE International Conference on Image Processing (ICIP), pp. 1410–1414 (2014)
Acknowledgements
This work was supported in part by Accenture, project CogniMetrics from MINECO/FEDER under Grant TEC2015-70627-R, and project Neurometrics (CEALAL/2017-13) from UAM-Banco Santander. The work of J. Hernandez-Ortega was supported by a Ph.D. Scholarship from Universidad Autonoma de Madrid.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Hernandez-Ortega, J., Fierrez, J., Gonzalez-Sosa, E., Morales, A. (2019). Continuous Presentation Attack Detection in Face Biometrics Based on Heart Rate. In: Bai, X., et al. Video Analytics. Face and Facial Expression Recognition. FFER DLPR 2018 2018. Lecture Notes in Computer Science(), vol 11264. Springer, Cham. https://doi.org/10.1007/978-3-030-12177-8_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-12177-8_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-12176-1
Online ISBN: 978-3-030-12177-8
eBook Packages: Computer ScienceComputer Science (R0)