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P306 - BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group

https://dl.gi.de/handle/20.500.12116/34315
Auflistung nach:

Auflistung P306 - BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group nach Autor:in "Boutros, Fadi"

1 - 2 von 2
  • Konferenzbeitrag
    Compact Models for Periocular Verification Through Knowledge Distillation
    (BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Boutros, Fadi; Damer, Naser; Fang, Meiling; Raja, Kiran; Kirchbuchner, Florian; Kuijper, Arjan
    Despite the wide use of deep neural network for periocular verification, achieving smaller deep learning models with high performance that can be deployed on low computational powered devices remains a challenge. In term of computation cost, we present in this paper a lightweight deep learning model with only 1.1m of trainable parameters, DenseNet-20, based on DenseNet architecture. Further, we present an approach to enhance the verification performance of DenseNet-20 via knowledge distillation. With the experiments on VISPI dataset captured with two different smartphones, iPhone and Nokia, we show that introducing knowledge distillation to DenseNet-20 training phase outperforms the same model trained without knowledge distillation where the Equal Error Rate (EER) reduces from 8.36% to 4.56% EER on iPhone data, from 5.33% to 4.64% EER on Nokia data, and from 20.98% to 15.54% EER on cross-smartphone data.
  • Konferenzbeitrag
    The Effect of Wearing a Mask on Face Recognition Performance: an Exploratory Study
    (BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Damer, Naser; Grebe, Jonas Henry; Chen, Cong; Boutros, Fadi; Kirchbuchner, Florian; Kuijper, Arjan
    Face recognition has become essential in our daily lives as a convenient and contactless method of accurate identity verification. Process such as identity verification at automatic border control gates or the secure login to electronic devices are increasingly dependant on such technologies. The recent COVID-19 pandemic have increased the value of hygienic and contactless identity verification. However, the pandemic led to the wide use of face masks, essential to keep the pandemic under control. The effect of wearing a mask on face recognition in a collaborative environment is currently sensitive yet understudied issue. We address that by presenting a specifically collected database containing three session, each with three different capture instructions, to simulate realistic use cases.We further study the effect of masked face probes on the behaviour of three top-performing face recognition systems, two academic solutions and one commercial off-the-shelf (COTS) system.