Five videos of 300 frames were captured for each session. The data was collected in 3 different sessions from the subjects. Each frame consists of a depth image, the corresponding RGB image and manually annotated eye positions (with respect to the RGB image). These were recorded using Kinect for both real access and spoofing attacks. It currently comprises 76500 frames covering 17 people. The 3D Mask Attack Database (3DMAD) is a biometric (face) spoofing database. Many of these databases have specific requirements in regards to referencing. In most cases they will be shown on, or linked to, the database's webpage. Make certain that you read the terms of use for any database you intend to use. In particular, most of these databases are only available for non-commercial research purposes. There are different rules and requirements when it comes to the usage of each of these databases. Here is a selection of facial recognition databases that are available on the internet. Why reinvent the wheel if you do not have to! Alternatively, you could look at some of the existing facial recognition and facial detection databases that fellow researchers and organizations have created in the past. You could, perhaps, find and possibly pay hundreds of people to have their face enrolled in the system. One thing you are going to want is a variety of faces that you can use for your system. Suppose you are a researcher wanting to investigate some aspect of facial recognition or facial detection.

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