Abstract
The aim of this paper is to present an automatic update rule to make a face recognition system adapt itself to the continuously changing appearance of users. The main idea is that every time the system interacts with a user, it adapts itself to include his or her current appearance, and thus, it always stays up-to-date. We propose a novel quality measure, which is used to decide whether the information just learnt from a user can be used to aggregate to what the system already knows. In the absence of databases that suit our needs, we present a publicly available database with 14,279 images of 35 users and 74 impostors acquired in a span of 5 months. Experiments on this database show that the proposed measure is adequate for a system to learn the current appearance of users in a non-supervised manner.
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Aryananda, L.: Recognizing and remembering individuals: online and unsupervised face recognition for humanoid robot. In: IROS 2002, pp. 1202–1207 (2002)
Cootes, T., Edwards, G., Taylor, C.: Active appearance models. IEEE Trans. Pattern Anal. Mach. Intell. 23(6), 681–685 (2001)
Lanitis, A., Taylor, C., Cootes, T.: Modeling the process of ageing in face images. In: ICCV 1999, pp. 131–136 (1999)
Lanitis, A., Taylor, C., Cootes, T.: Toward automatic simulation of aging effects on face images. IEEE Trans. Pattern Anal. Mach. Intell. 24(4), 442–455 (2002)
Messer, K., et al.: Face verification competition on the XM2VTS database. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688, pp. 964–974. Springer, Heidelberg (2003)
Messer, K., Matas, J., Kittler, J., Luettin, J., Maitre, G.: XM2VTSDB: The extended M2VTS database. In: AVBPA 1999, pp. 72–77 (1999)
Mou, D., Schweer, R., Rothermel, A.: Automatic databases for unsupervised face recognition. In: CVPRW 2004, pp. 90–97 (2004)
Navarrete, P., Ruiz-del-Solar, J.: Comparative study between different eigenspace-based approaches for face recognition. In: Pal, N.R., Sugeno, M. (eds.) AFSS 2002. LNCS, vol. 2275, pp. 178–184. Springer, Heidelberg (2002)
Perlibakas, V.: Distance measures for PCA-based face recognition. Pattern Recogn. Lett. 25(6), 711–724 (2004)
Phillips, P., et al.: Face recognition vendor test 2002. Evaluation Report (2003), http://www.frvt.org
Sukno, F., Frangi, A.: Exploring reliability for automatic identity verification with statistical shape models. In: AutoID 2007, pp. 80–86 (2007)
Sukno, F., et al.: Active shape models with invariant optimal features. IEEE Trans. Pattern Anal. Mach. Intell. 29(7), 1105–1117 (2007)
Viola, P., Jones, M.: Robust real-time face detection. Int. J. Comput. Vision 57(2), 137–154 (2004)
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Pavani, SK., Sukno, F.M., Butakoff, C., Planes, X., Frangi, A.F. (2009). A Confidence-Based Update Rule for Self-updating Human Face Recognition Systems. In: Tistarelli, M., Nixon, M.S. (eds) Advances in Biometrics. ICB 2009. Lecture Notes in Computer Science, vol 5558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01793-3_16
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DOI: https://doi.org/10.1007/978-3-642-01793-3_16
Publisher Name: Springer, Berlin, Heidelberg
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