UnissResearch

Logo Universitàegli studi di Sassari
titoli, abstracts, parole chiave >>>
Probabilistic face authentication using Hidden Markov Models

Bicego, Manuele and Grosso, Enrico and Tistarelli, Massimo (2005) Probabilistic face authentication using Hidden Markov Models. In: Biometric Technology for Human Identification II: proceedings of SPIE, 28-29 March 2005, Orlando (FL), USA. Bellingham, SPIE. Vol. 5779. p. 1-6. ISBN 0-8194-5764-7. Conference or Workshop Item.

Full text not available from this repository.

DOI: 10.1117/12.603286

Abstract

In this paper a novel approach for face authentication is proposed, based on the HiddenMarkov Model (HMM) tool. While this technique has been successfully employed in face recognition systems, its use in the authentication context has never been investigated. The method proposed in this paper extracts from the image a sequence of partially over- lapped images, from which different kinds of simple and quickly computable features are extracted. The face tem- plate is obtained by modelling the sequence with a contin- uous Gaussian Hidden Markov Model. Given an unknown subject, the authentication phase is carried out by thresholding the likelihood of the given face with respect to the HMM template. The proposed approach has been thor- oughly tested on the ORL database, also applying different parameters' configurations. A comparison with two other state-of-the-art approaches is also reported. The results obtained are really promising, showing the wide applicability of the Hidden Markov Models methodology.

Item Type:Conference or Workshop Item (Paper)
ID Code:313
Status:Published
Uncontrolled Keywords:Authentication, classification, Hidden Markov model, biometrics
Subjects:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 Sistemi di elaborazione delle informazioni
Divisions:001 Università di Sassari > 01 Dipartimenti > Economia, impresa, regolamentazione
001 Università di Sassari > 01 Dipartimenti > Architettura e pianificazione
Publisher:SPIE
ISBN:0-8194-5764-7
Deposited On:18 Aug 2009 10:02

I documenti depositati in UnissResearch sono protetti dalle leggi che regolano il diritto d'autore

Repository Staff Only: item control page