REPORT Raghavendra_Idiap-RR-17-2020/IDIAP Smartphone Multi-modal Biometric Authentication: Database and Evaluation Raghavendra, Ramachandra Stokkenes, Martin Mohammadi, Amir Venkatesh, Sushma Raja, Kiran B. Wasnik, Pankaj Poiret, Eric Marcel, Sébastien Busch, Christoph Biometrics database presentation attacks Smartphones Spoofing EXTERNAL https://publications.idiap.ch/attachments/reports/2019/Raghavendra_Idiap-RR-17-2020.pdf PUBLIC Idiap-RR-17-2020 2020 Idiap July 2020 Biometric-based verification is widely employed on the smartphones for various applications, including financial transactions. In this work, we present a new multimodal biometric dataset (face, voice, and periocular) acquired using a smartphone. The new dataset is comprised of 150 subjects that are captured in six different sessions reflecting real-life scenarios of smartphone assisted authentication. One of the unique features of this dataset is that it is collected in four different geographic locations representing a diverse population and ethnicity. Additionally, we also present a multimodal Presentation Attack (PA) or spoofing dataset using a low-cost Presentation Attack Instrument (PAI) such as print and electronic display attacks. The novel acquisition protocols and the diversity of the data subjects collected from different geographic locations will allow developing a novel algorithm for either unimodal or multimodal biometrics. Further, we also report the performance evaluation of the baseline biometric verification and Presentation Attack Detection (PAD) on the newly collected dataset. https://arxiv.org/abs/1912.02487 URL