%Aigaion2 BibTeX export from Idiap Publications %Friday 13 December 2024 11:17:59 AM @TECHREPORT{George_Idiap-RR-02-2022, author = {George, Anjith and Geissbuhler, David and Marcel, S{\'{e}}bastien}, projects = {Idiap, ODIN/BATL}, month = {2}, title = {A Comprehensive Evaluation on Multi-channel Biometric Face Presentation Attack Detection}, type = {Idiap-RR}, number = {Idiap-RR-02-2022}, year = {2022}, institution = {Idiap}, abstract = {The vulnerability against presentation attacks is a crucial problem undermining the wide-deployment of face recognition systems. Though presentation attack detection (PAD) systems try to address this problem, the lack of generalization and robustness continues to be a major concern. Several works have shown that using multi-channel PAD systems could alleviate this vulnerability and result in more robust systems. However, there is a wide selection of channels available for a PAD system such as RGB, Near Infrared, Shortwave Infrared, Depth, and Thermal sensors. Having a lot of sensors increases the cost of the system, and therefore an understanding of the performance of different sensors against a wide variety of attacks is necessary while selecting the modalities. In this work, we perform a comprehensive study to understand the effectiveness of various imaging modalities for PAD. The studies are performed on a multi-channel PAD dataset, collected with 14 different sensing modalities considering a wide range of 2D, 3D, and partial attacks. We used the multi-channel convolutional network-based architecture, which uses pixel-wise binary supervision. The model has been evaluated with different combinations of channels, and different image qualities on a variety of challenging known and unknown attack protocols. The results reveal interesting trends and can act as pointers for sensor selection for safety-critical presentation attack detection systems. The source codes and protocols to reproduce the results are made available publicly making it possible to extend this work to other architectures.}, pdf = {https://publications.idiap.ch/attachments/reports/2021/George_Idiap-RR-02-2022.pdf} }