Replay-Mobile is a dataset for face recognition and presentation attack detection (anti-spoofing). The dataset consists of 1190 video clips of photo and video presentation attacks (spoofing attacks) to 40 clients, under different lighting conditions. These videos were recorded with an iPad Mini2 (running iOS) and a LG-G4 smartphone (running Android).
All videos have been captured using the front-camera of the mobile device (tablet or phone). The front-camera produces colour videos with a resolution of 720 pixels (width) by 1280 pixels (height) and saved in ".mov" file-format. The frame rate is about 25 Hz. Real-accesses have been performed by the genuine user (presenting one's true face to the device). Attack-accesses have been performed by displaying a photo or a video recording of the attacked client, for at least 10 seconds.
Real client accesses have been recorded under five different lighting conditions (controlled, adverse, direct, lateral and diffuse). In addition, to produce the attacks, high-resolution photos and videos from each client were taken under conditions similar to those in their authentication sessions (lighton, lightoff).
The 1190 real-accesses and attacks videos were then grouped in the following way:
For photos attacks a Nikon coolix P520 camera, which records 18Mpixel photographs, has been used. Video attacks were captured using the back-camera of a smartphone LG-G4, which records 1080p FHD video clips using its 16 Mpixel camera.
Attacks have been performed in two ways:
(1) A matte-screen was used to perform the attacks (i.e., to display the digital photo or video of the attacked identity). For all such (matte-screen) attacks, a stand was used to hold capturing devices.
(2) Print attacks. For "fixed" attacks, both capturing devices were supported on a stand (as for matte-screen attacks). For "hand" attacks, the spoofer held the capturing device in his/her own hands while the spoof-resource (printed photo) was stationary.
In total, 16 attack videos were registered for each client, 8 for each of the attacking modes described above.
If you use this database, please cite the following publication:
Artur Costa-Pazo, Sushil Bhattacharjee, Esteban Vazquez-Fernandez and Sébastien Marcel,"The REPLAY-MOBILE Face Presentation-Attack Database", IEEE BIOSIG 2016.
10.1109/BIOSIG.2016.7736936
https://publications.idiap.ch/index.php/publications/show/3477