Abstract
How can scientific progress be measured? How do we know if a pattern recognition algorithm performs better on average than another one? How much data is needed to claim with confidence that one system performs better than another one? Is it possible to predict performance on a different data set? How will the performance rates achieved under laboratory conditions compare to those in larger populations? These are some of the questions that are central to this book. Biometrics is the application domain under concern. For applications related to verification, a person claims an identity. The system has in memory some training data for this identity claim (or a statistical model of it) and performs a comparison (or computes a likelihood) with the test data. The output is a score that is compared to a threshold to take a decision: accept or reject the identity claim. For applications related to identification, the system has in memory a list of identities and their training data. When a person presents biometric data, the system has to find out to whom the data belong. These two tasks, verification and identification, are grouped under the term of biometric recognition throughout this book.
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BECARS. http://www.tsi.enst.fr/becars.
S. Bengio, C. Marcel, S. Marcel, and J. Mariéthoz. Confidence measures for multimodal identity verification. Information Fusion, 3, 2002.
J. O. Berger. A Statistical Decision Theory. Springer-Verlag, 1980.
F. Bimbot and G. Chollet. Handbook of Standards and Resources for Spoken Language Systems. Mouton de Gruyter, 1998.
BioSecure Mutimodal Evaluation Campaign 2007 (BMEC'2007). http://www.biometrics. it-sudparis.eu/BMEC2007/.
BioSecure NoE. http://biosecure.info.
J. B. Buckheit and D. L. Donoho. WaveLab and Reproducible Research. Stanford University, Stanford CA 94305, US.
G. Chollet and C. Gagnoulet. On the evaluation of speech recognizers and databases using a reference system. ICASSP, 38(1):2026–2029, 1982.
R. J. Connell, S. Pankanti, N. Ratha, and A. Senior. Guide to Biometrics. Springer, 2003.
FERET database. Url:http://www.itl.nist.gov/iad/humanid/feret.
G. Doddington. Speaker recognition – identifying people by their voices. In Proc. of the IEEE, 1985.
G. Doddington, W. Ligget, A. Matrin, M. Przybocki, and D. Reynolds. Sheeps, goats, lambs, and wolves: A statistical analysis of speaker performance in the nist 1998 speaker recognition evaluation. In Proceedings of ICSLP, 1998.
B. Efron and R. J. Tibshirani. An Introduction to the Bootstrap. Chapman & Hall/CRC, 1993.
BioSecure Benchmarking Framework. http://share.int-evry.fr/svnview-eph/.
IV2: Identification par l'Iris et le Visage via la Vidéo. http://iv2.ibisc.fr/PageWeb-IV2.html.
A. K. Jain, P. Flynn, and A. A. Ross. Handbook of Biometrics. Springer-Verlag, 2008.
Julius. http://julius.sourceforge.jp/en/.
S. Mallat. A Wavelet Tour of Signal Processing. Academic Press, 1999.
A. Martin, G. Doddington, T. Kamm, M. Ordowski, and M. Przybocki. The det curve in assessment of detection task performance. Proc. Eurospeech, 1997.
T. Matsumoto. Impact of artificial gymmy fingers on fingerprint systems. In Proceedings of SPIE - Optical Security and Counterfeit Deterrence Techniques IV, volume 4677, January 2002.
P. J. Phillips, W. T. Scruggs, A. J. OToole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe. FRVT 2006 and ICE 2006 Large-Scale Results (NISTIR 7408), March 2007.
N. K. Ratha and V. Govindaraju. Advances in Biometrics: Sensors, Algorithms and Systems. Springer-Verlag, 2007.
A. Schmidt-Nielsen and T. H. Crystal. Speaker verification by human listeners: Experiments comparing human and machine performance using the nist 1998 speaker evaluation data. Digital Signal Processing, 10:249266, 2000.
SPHINX. http://cmusphinx.sourceforge.net/html/cmusphinx.php.
Torch. http://www.torch.ch/.
wavelab. http://www-stat.stanford.edu/ wavelab/.
M. Wittman, P. Davis, and P. J. Flynn. Empirical studies of the existence of the biometric menagerie in the frgc 2.0 color image corpus. In Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop, June 2006.
Acknowledgments
Thanks to J. Darbôn who pointed out to us the adoption by S. Mallat of the reproducible research philosophy of Stanford University.
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Chollet, G., Dorizzi, B., Petrovska-Delacrétaz, D. (2009). Introduction—About the Need of an Evaluation Framework in Biometrics. In: Petrovska-Delacrétaz, D., Dorizzi, B., Chollet, G. (eds) Guide to Biometric Reference Systems and Performance Evaluation. Springer, London. https://doi.org/10.1007/978-1-84800-292-0_1
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DOI: https://doi.org/10.1007/978-1-84800-292-0_1
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