Abstract
Biometric identification technology is being applied to physical and information access control in some workplace with the improvements in the accuracy of biometric devices and declining price. This paper describes a multimodal biometric identification system for time and attendance application called AVAS (Audio-Visual Attendance System). This system takes users’ voice and face characteristics as their badge. The motivation behind using multimodal biometrics is to improve availability and accuracy of the system. The score differences between the genuine speaker class and the mistaken identified speaker class labeled by each classifier are taken into account, and Score Difference Weighted Sum rule (SDWS) is introduced to fuse the individual expert. We describe the functions of the AVAS in detail from three aspects, the interaction with users, the authentication implementation and the data management. The practical tests conducted on staff working environment gain distinct improvement about 9.8% with the proposed system.
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References
Takahashi, K., Mimura, M., Isobe, Y., Seto, Y.: A secure and user-friendly multi-modal biometric system. In: Biometric Technology for Human Identification, Proceedings of SPIE, vol. 5404, pp. 12–19 (2004)
Sanchez-Reillo, R., Sanchez-Avila, C.: Fingerprint verification using smart cards for access control systems. Aerospace and Electronic Systems Magazine, IEEE 17(9), 12–15 (2002)
Roli., F., Kittler., J., Fumera., G., Muntoni, D.: An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems. In: Multiple Classifier Systems, pp. 325–336 (2002)
Speaker Verification Library, http://www.patni.com/innovate/innovate_prods_voicesafe.htm
Ross, A., Jain, A.K., Qian, J.Z.: Information Fusion in Biometrics. In: Proc. 3rd International Conference on Audio- and Video-Based Person Authentication (AVBPA), Sweden, pp. 354–359 (2001)
Ben-Yacoub, S., Abdeljaoued, Y., Mayoraz, E.: Fusion of face and speech data for person identity verification. IEEE Transactions on Neural Networks, 1065–1074 (1999)
Li, D.D., Yang, Y.C., Wu, Z.H.: Combining Voiceprint and Face Biometrics for Speaker Identification Using SDWS. In: Proceedings of the 9th Eurospeech, pp. 1209–1212 (2005)
Wang, Y.M., Pan, G., Yang, Y.C., Li, D.D., Wu, Z.H.: Enhancing 3D Face Recognition by Combination of Voiceprint. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2006. LNCS, vol. 3991, pp. 435–442. Springer, Heidelberg (2006)
Reynolds, D.A.: A Gaussian Mixture Modeling Approach to Text-Independent Speaker Identification. IEEE Trans. Speech Audio Process 3, 72–83 (1995)
Wang., Y., Tan, T., Jain, A.K.: Combining Face and Iris Biometrics for Identity Verification. In: Proc.of 4th Int’l Conf.on Audio- and Video-Based Biometric Person Authentication (AVBPA), pp. 805–813 (2003)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. Computer Vision and Pattern Recognition 1, 511–518 (2001)
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Li, D., Yang, Y., Shan, Z., Pan, G., Wu, Z. (2006). AVAS: An Audio-Visual Attendance System. In: Zhuang, Y., Yang, SQ., Rui, Y., He, Q. (eds) Advances in Multimedia Information Processing - PCM 2006. PCM 2006. Lecture Notes in Computer Science, vol 4261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11922162_77
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DOI: https://doi.org/10.1007/11922162_77
Publisher Name: Springer, Berlin, Heidelberg
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