Abstract
In the well explored domain of facial biometrics, methods which forgo traditional models of intruder detection can lead to a more robust system. One such method, which is outlined in this paper, is to utilize the movement of feature points over the course of an expression to make user authentication systems more secure. To do this, we developed a new algorithm, and used the process known as ranking, to describe facial expressions in a computationally cheap way. In our experiments, we performed 309,210 authentication attempts on 33 user profiles and achieved at best an error of only 3.4 %, with an average error of 33.28 %. Although such a system is not as accurate as common face biometric systems, we believe that this method can augment those systems to make them impervious to common attacks.
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Acknowledgements
This research was supported by the Michigan Space Grant Consortium. We thank our colleagues in the College of Science, Engineering, and Technology at Saginaw Valley State University for their continued support. In addition, we thank the Undergraduate Research Program (UGRP) at Saginaw Valley State University for making our continued works possible. In addition, we thank the students at Saginaw Valley State University for their valuable data and Cody Brown, whose assistance was invaluable.
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Tubbs, D.J., Rahman, K.A. (2015). Facial Expression Analysis as a Means for Additional Biometric Security in Recognition Systems. In: Dziech, A., Leszczuk, M., Baran, R. (eds) Multimedia Communications, Services and Security. MCSS 2015. Communications in Computer and Information Science, vol 566. Springer, Cham. https://doi.org/10.1007/978-3-319-26404-2_9
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DOI: https://doi.org/10.1007/978-3-319-26404-2_9
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