The FRAUD Datasets are the first practical attempt to counter replay attacks for face recognition systems that use uncontrolled consumer devices. The final operation of the system is designed to illuminate the face of the user with images displayed on the computer screen, and then using the camera to capture the face images that will be used for the face recognition system. In addition to liveness and anti-spoofing tests, the image reflection might be observed in the face.
If the reflection sequence matches the images that were displayed, it can be assumed that the video was created at the time that the images were displayed.
In the case of this dataset, the videos have been previously captured at the time the nominated images were displayed. In its final form, it is expected that the images will be nominated in real-time.
Researchers are invited to use these datasets to improve techniques for classifying image reflection from objects, and to validate the results obtained in our experiments.
Last updated: 04-Feb-2015