The 3D Mask Attack Database (3DMAD) is a biometric (face) spoofing database. It currently contains 76500 frames of 17 persons, recorded using Kinect for both real-access and spoofing attacks. Each frame consists of:

1. • a depth image (640x480 pixels – 1x11 bits)
   

2. • the corresponding RGB image (640x480 pixels – 3x8 bits)
   

3. • manually annotated eye positions (with respect to the RGB image).
   

 

The data is collected in 3 different sessions for all subjects and for each session 5 videos of 300 frames are captured. The recordings are done under controlled conditions, with frontal-view and neutral expression. The first two sessions are dedicated to the real access samples, in which subjects are recorded with a time delay of ~2 weeks between the acquisitions. In the third session, 3D mask attacks are captured by a single operator (attacker).

The database is available here: https://www.idiap.ch/dataset/3dmad

If you use this database please cite this publication:

N. Erdogmus and S. Marcel. “Spoofing in 2d face recognition with 3d masks and anti-spoofing with Kinect”. In IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS), 2013.

Pdf: http://publications.idiap.ch/downloads/papers/2013/Erdogmus_BTAS_2013.pdf 

Source code to reproduce experiments in the paper:

https://pypi.python.org/pypi/maskattack.lbp