A Novel Application of Universal Background Models for Periocular Recognition

  • João C. MonteiroEmail author
  • Jaime S. Cardoso
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 574)


In recent years the focus of research in the fields of iris and face recognition has turned towards alternative traits to aid in the recognition process under less constrained acquisition scenarios. The present work assesses the potential of the periocular region as an alternative to both iris and face in such conditions. An automatic modeling of SIFT descriptors, using a GMM-based Universal Background Model method, is proposed. This framework is based on the Universal Background Model strategy, first proposed for speaker verification, extrapolated into an image-based application. Such approach allows a tight coupling between individual models and a robust likelihood-ratio decision step. The algorithm was tested on the UBIRIS.v2 and the MobBIO databases and presented state-of-the-art performance for a variety of experimental setups.


Biometrics Iris segmentation Unconstrained environment Gradient flow Shortest closed path 



The first author would like to thank Fundação para a Ciência e Tecnologia (FCT) - Portugal the financial support for the PhD grant SFRH/BD/87392/ 2012.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.INESC TEC and Faculdade de EngenhariaUniversidade do Porto Campus da FEUPPortoPortugal

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