Abstract
This paper describes a novel framework for the Open World face recognition problem, where one has to provide for the Reject option. Based upon algorithmic randomness and transduction, a particular form of induction, we describe the TCM-kNN (Transduction Confidence Machine - kNearest Neighbor) algorithm for Open World face recognition. The algorithm proposed performs much better than PCA and is comparable with Fisherfaces. In addition to recognition and rejection, the algorithm can assign credibility (“likelihood”) and confidence (“lack of ambiguity”) measures with the identification decisions taken.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gammerman, V. Vovk, and V. Vapnik (1998), Learning by Transduction. In Uncertainty in Artificial Intelligence, 148–155.
M. Li and P. Vitanyi (1997), An Introduction to Kolmogorov Complexity and Its Applications, 2ed., Springer-Verlag.
Liu and H. Wechsler (2002), Gabor Feature Based Classification Using the Enhnaced Fisher Linera Discriminant Model for Face Recognition, IEEE Trans. on Image Processing, Vol. 11, No. 4, 467–476.
Nouretdinov, T. Melluish, and V. Vovk (2001), Ridge Regression Confidence Machine, Proc. 17th Int. Conf. on Machine Learning.
P. J. Phillips, H. Wechsler, J. Huang, and P. Rauss (1998), The FERET Database and Evaluation Procedure for Face Recognition Algorithms, Image and Vision Computing, Vol.16, No.5, 295–306.
K. Proedrou, I. Nouretdinov, V. Vovk and A. Gammerman (2001), Transductive Confidence Machines for Pattern Recognition, TR CLRC-TR-01-02, Royal Holloway University of London.
V. Vovk, A. Gammerman, and C. Saunders (1999), Machine Leraning Applications of Algorithmic Randomness, Proc. 16th Int. Conf. on Machine Learning.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, F., Wechsler, H. (2003). Open World Face Recognition with Credibility and Confidence Measures. In: Kittler, J., Nixon, M.S. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2003. Lecture Notes in Computer Science, vol 2688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44887-X_55
Download citation
DOI: https://doi.org/10.1007/3-540-44887-X_55
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40302-9
Online ISBN: 978-3-540-44887-7
eBook Packages: Springer Book Archive