Abstract
This paper proposes a new method for personal identity verification based the analysis of face images applying One Class Support Vector Machines. This is a recently introduced kernel method to build a unary classifier to be trained by using only positive examples, avoiding the sensible choice of the impostor set typical of standard binary Support Vector Machines. The features of this classifier and the application to face-based identity verification are described and an implementation presented. Several experiments have been performed on both standard and proprietary databases. The tests performed, also in comparison with a standard classifier built on Support Vector Machines, clearly show the potential of the proposed approach.
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Bicego, M., Grosso, E., Tistarelli, M. (2005). Face Authentication Using One-Class Support Vector Machines. In: Li, S.Z., Sun, Z., Tan, T., Pankanti, S., Chollet, G., Zhang, D. (eds) Advances in Biometric Person Authentication. IWBRS 2005. Lecture Notes in Computer Science, vol 3781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11569947_3
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DOI: https://doi.org/10.1007/11569947_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29431-3
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