In response to the rising threat of the face morphing attack, this paper introduces and explores the potential of Video-based Morphing Attack Detection (V-MAD) systems in real-world operational scenarios. While current morphing attack detection methods primarily focus on a single or a pair of images, V-MAD is based on video sequences, exploiting the video streams acquired by face verification tools available, for instance, at airport gates. We show for the first time the advantages that the availability of multiple probe frames brings to the morphing attack detection task, especially in scenarios where the quality of probe images is varied. Experimental results on a real operational database demonstrate that video sequences represent valuable information for increasing the performance of morphing attack detection systems.

V-MAD: Video-based Morphing Attack Detection in Operational Scenarios / Borghi, G.; Franco, A.; Di Domenico, N.; Ferrara, M.; Maltoni, D.. - (2024), pp. 1-10. (Intervento presentato al convegno 18th IEEE International Joint Conference on Biometrics, IJCB 2024 tenutosi a usa nel 2024) [10.1109/IJCB62174.2024.10744469].

V-MAD: Video-based Morphing Attack Detection in Operational Scenarios

Borghi G.
;
2024

Abstract

In response to the rising threat of the face morphing attack, this paper introduces and explores the potential of Video-based Morphing Attack Detection (V-MAD) systems in real-world operational scenarios. While current morphing attack detection methods primarily focus on a single or a pair of images, V-MAD is based on video sequences, exploiting the video streams acquired by face verification tools available, for instance, at airport gates. We show for the first time the advantages that the availability of multiple probe frames brings to the morphing attack detection task, especially in scenarios where the quality of probe images is varied. Experimental results on a real operational database demonstrate that video sequences represent valuable information for increasing the performance of morphing attack detection systems.
2024
18th IEEE International Joint Conference on Biometrics, IJCB 2024
usa
2024
1
10
Borghi, G.; Franco, A.; Di Domenico, N.; Ferrara, M.; Maltoni, D.
V-MAD: Video-based Morphing Attack Detection in Operational Scenarios / Borghi, G.; Franco, A.; Di Domenico, N.; Ferrara, M.; Maltoni, D.. - (2024), pp. 1-10. (Intervento presentato al convegno 18th IEEE International Joint Conference on Biometrics, IJCB 2024 tenutosi a usa nel 2024) [10.1109/IJCB62174.2024.10744469].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1367123
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