D4FLY multimodal biometric database: multimodal fusion evaluation envisaging on-the-move biometric-based border control

Chen, L., Boyle, J. ORCID: https://orcid.org/0000-0002-5785-8046, Danelakis, A., Ferryman, J., Ferstl, S., Gicic, D., Grudzień, A., Howe, A., Marcin, K., Mierzejewski, K. and Theoharis, T. (2021) D4FLY multimodal biometric database: multimodal fusion evaluation envisaging on-the-move biometric-based border control. In: 2021 17th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 16-19 NOV 2021, Virtual. doi: 10.1109/AVSS52988.2021.9663737

Abstract/Summary

This work presents a novel multimodal biometric dataset with emerging biometric traits including 3D face, thermal face, iris on-the-move, iris mobile, somatotype and smartphone sensors. This dataset was created to resemble on-the-move characteristics in applications such as border control. The five types of biometric traits were selected as they can be captured while on-the-move, are contactless, and show potential for use in a multimodal fusion verification system in a border control scenario. Innovative sensor hardware was used in the data capture. The data featuring these biometric traits will be a valuable contribution to advancing biometric fusion research in general. Baseline evaluation was performed on each unimodal dataset. Multimodal fusion was evaluated based on various scenarios for comparison. Real-time performance is presented based on an Automated Border Control (ABC) scenario.

Item Type	Conference or Workshop Item (Paper)
URI	https://reading-clone.eprints-hosting.org/id/eprint/101891
Item Type	Conference or Workshop Item
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
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