There were no restrictions placed on clothes, glasses, make-up or hair style. The pictures were taken under strictly controlled conditions. The images are frontal view faces depicting different facial expressions, illumination conditions, and add-ons like sunglasses and scarves. It contains over 4,000 color images of 126 people's faces (70 men and 56 women). This face database was created by Aleix Martinez and Robert Benavente at the Computer Vision Center (CVC) at the University of Alabama at Birmingham (U.A.B.). The AR Face Database, The Ohio State University The database includes a software tool that allows you to export custom image sets from the database for your research.Ĥ. The attribute data are stored in either MATLAB or Excel files. The face images are JPEGs with 72 pixels/in resolution and 256-pixel height. This database contains 10,168 natural face photographs and several measures for 2,222 of the faces, including memorability scores and computer vision and psychology attributes. For each session, three shots were recorded with different (but limited) orientations of the head: straight forward / left or right / upward or downward. 120 people were asked to pose twice in front of the system. The facial surface was acquired as a set of 3D coordinates using a projector and a camera. This database was created with a 3D acquisition system based on structured light. The recordings were done under controlled conditions and depict frontal view and neutral expression. 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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