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Efficient adaptive face recognition systems based on capture conditions


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Pagano, C., Granger, É., Sabourin, R., Rattani, A., Marcialis, G. L. et Roli, F.. 2014. « Efficient adaptive face recognition systems based on capture conditions ». In 2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM). Proceedings (Orlando, FL, U.S.A, Dec. 9-12, 2014) pp. 60-67. Piscataway, NJ, USA : IEEE.

Granger E. 2014 11315 Efficient adaptive face recognition systems based on capture.pdf

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In many face recognition (FR) applications, changing capture conditions lead to divergence between facial models stored during enrollment and faces captured during operations. Moreover, it is often costly or infeasible to capture several high quality reference samples a priori to design representative facial models. Although self-updating models using high-confidence face captures appear promising, they raise several challenges when capture conditions change. In particular, face models of individuals may be corrupted by misclassified input captures, and their growth may require pruning to bound system complexity over time. This paper presents a system for self-update of facial models that exploits changes in capture conditions to assure the relevance of templates and to limit the growth of template galleries. The set of reference templates (facial model) of an individual is only updated to include new faces that are captured under significantly different conditions. In a particular implementation of this system, illumination changes are detected in order to select face captures from bio-login to be stored in a gallery. Face captures from a built-in still or video camera are taken at periodic intervals to authenticate the user having accessed a secured computer or network. Experimental results produced with the DIEE dataset show that the proposed system provides a comparable level of performance to the FR system that self-updates the gallery on all high-confidence face captures, but with significantly lower complexity, i.e., number of templates per individual.

Item Type: Conference proceeding
Granger, Éric
Sabourin, Robert
Affiliation: Génie de la production automatisée
Date Deposited: 21 Sep 2015 17:47
Last Modified: 19 Jan 2016 22:10

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