© The Institution of Engineering and Technology
There is no abstract available for this article.
References
-
-
1)
-
15. Poh, N., Martin, A., Bengio, S.: ‘Performance generalization in biometric authentication using joint user-specific and sample bootstraps’, IEEE Trans. Pattern Anal. Mach. Intell., 2007, 29, pp. 492–498 (doi: 10.1109/TPAMI.2007.55).
-
2)
-
13. Wang, P., Ji, Q., Wayman, J.L.: ‘Modeling and predicting face recognition system performance based on analysis of similarity scores’, IEEE Trans. Pattern Anal. Mach. Intell., 2007, 29, (4), pp. 665–670 (doi: 10.1109/TPAMI.2007.1015).
-
3)
-
3. Pankanti, S., Prabhakar, S., Jain, A.: ‘On the individuality of fingerprints’, IEEE Trans. Pattern Anal. Mach. Intell., 2002, 24, (8), pp. 1010–1025 (doi: 10.1109/TPAMI.2002.1023799).
-
4)
-
17. Poh, N., Bengio, S.: ‘How do correlation and variance of base classifiers affect fusion in biometric authentication tasks?’, IEEE Trans. Signal Process., 2005, 53, (11), pp. 4384–4396 (doi: 10.1109/TSP.2005.857006).
-
5)
-
1. Schuckers, M.E.: ‘Computational methods in biometric authentication: statistical methods for performance evaluation’ (Springer Science & Business Media, 2010).
-
6)
-
12. Yui Man, L., Bolme, D., Draper, B.A., et al: ‘A meta-analysis of face recognition covariates. Biometrics: Theory, Applications, and Systems, 2009’. IEEE 3rd Int. Conf. on BTAS '09. 2009.
-
7)
-
32. Dass, S.C., Zhu, Y., Jain, A.K.: ‘Validating a biometric authentication system: sample size requirements’, IEEE Trans. Pattern Anal. Mach., 2006, 28, (12), pp. 1902–1319 (doi: 10.1109/TPAMI.2006.255).
-
8)
-
5. Doddington, G., Liggett, W., Martin, A., et al: ‘Sheep, Goats, Lambs and Wolves: A Statistical Analysis of Speaker Performance in the NIST 1998 Speaker Recognition Evaluation’. Int. Conf. Spoken Language Processing (ICSLP). Sydney, 1998.
-
9)
-
6. Yager, N., Dunstone, T.: ‘The biometric menagerie’, IEEE Trans. Pattern Anal. Mach. Intell., 2010, 32, (2), pp. 220–230 (doi: 10.1109/TPAMI.2008.291).
-
10)
-
11. Beveridge, J.R., Givens, G.H., Phillips, P.J., et al: ‘Factors that influence algorithm performance in the face recognition grand challenge’, Comput. Vis. Image Underst., 2009, 113, (6), pp. 750–762 (doi: 10.1016/j.cviu.2008.12.007).
-
11)
-
10. Poh, N., Chi Ho, C.: ‘Generalizing DET curves across application scenarios’, IEEE Trans. Inf. Forensics Sec., 2015, 10, (10), pp. 2171–2181 (doi: 10.1109/TIFS.2015.2434320).
-
12)
-
14. Bolle, R.M., Ratha, N.K., Pankanti, S.: ‘Error analysis of pattern recognition systems the subsets bootstrap’, Comput. Vis. Image Underst., 2004, 93, pp. 1–33 (doi: 10.1016/j.cviu.2003.08.002).
-
13)
-
16. Grother, P., Matey, J.R., Tabassi, E., et al: ‘IREX VI. Temporal Stability of Iris Recognition Accuracy’. , 2013, 7948, pp. 1–3.
-
14)
-
4. Zhu, Y., Dass, S.C., Jain, A.: ‘Statistical models for assessing the individuality of fingerprints’, IEEE Trans. Inf. Forensics Sec., 2007, 2, (3), pp. 391–401 (doi: 10.1109/TIFS.2007.903846).
-
15)
-
15. Wayman, J.L., Possolo, A., Mansfield, A.J.: ‘Modern statistical and philosophical framework for uncertainty assessment in biometric performance testing’, IET Biometrics, 2013, 2, (3), pp. 85–96 (doi: 10.1049/iet-bmt.2013.0009).
-
16)
-
7. Poh, N., Kittler, J.: ‘A biometric menagerie index for characterising template/model-specific variation’. Proc. of the 3rd Int. Conf. on Biometrics.Sardinia, 2009, pp. 816–827.
-
17)
-
14. Poh, N., Bengio, S.: ‘Towards predicting optimal subsets of base-experts in biometric authentication task’. LNCS 3361. 1st Joint AMI/PASCAL/IM2/M4 Workshop on Multimodal Interaction and Related Machine Learning Algorithms MLMI. Martigny, 2004, pp. 159–172.
-
18)
-
18. Tresadern, P., Cootes, T.F., Poh, N., et al: ‘Mobile biometrics: combined face and voice verification for a mobile platform’, IEEE Pervasive Comput., 2013, 12, (1), pp. 79–87 (doi: 10.1109/MPRV.2012.54).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-bmt.2015.0100
Related content
content/journals/10.1049/iet-bmt.2015.0100
pub_keyword,iet_inspecKeyword,pub_concept
6
6