Face Recognition Grand Challenge - The FRGC Data Set

The FRGC Data Set

The FRGC data distribution consists of three parts. The first is the FRGC data set. The second part is the FRGC BEE. The BEE distribution includes all the data sets for performing and scoring the six experiments. The third part is a set of baseline algorithms for experiments 1 through 4. With all three components, it is possible to run experiments 1 through 4, from processing the raw images to producing Receiver Operating Characteristics (ROCs).

The data for FRGC consists of 50,000 recordings divided into training and validation partitions. The training partition is designed for training algorithms and the validation partition is for assessing performance of an approach in a laboratory setting. The validation partition consists of data from 4,003 subject sessions. A subject session is the set of all images of a person taken each time a person's biometric data is collected and consists of four controlled still images, two uncontrolled still images, and one three-dimensional image. The controlled images were taken in a studio setting, are full frontal facial images taken under two lighting conditions and with two facial expressions (smiling and neutral). The uncontrolled images were taken in varying illumination conditions; e.g., hallways, atriums, or outside. Each set of uncontrolled images contains two expressions, smiling and neutral. The 3D image was taken under controlled illumination conditions. The 3D images consist of both a range and a texture image. The 3D images were acquired by a Minolta Vivid 900/910 series sensor.

The FRGC distribution consists of six experiments. In experiment 1, the gallery consists of a single controlled still image of a person and each probe consists of a single controlled still image. Experiment 1 is the control experiment. Experiment 2 studies the effect of using multiple still images of a person on performance. In experiment 2, each biometric sample consists of the four controlled images of a person taken in a subject session. For example, the gallery is composed of four images of each person where all the images are taken in the same subject session. Likewise, a probe now consists of four images of a person.

Experiment 3 measures the performance of 3D face recognition. In experiment 3, the gallery and probe set consist of 3D images of a person. Experiment 4 measures recognition performance from uncontrolled images. In experiment 4, the gallery consists of a single controlled still image, and the probe set consists of a single uncontrolled still image.

Experiments 5 and 6 examine comparing 3D and 2D images. In both experiments, the gallery consists of 3D images. In experiment 5, the probe set consists of a single controlled still. In experiment 6, the probe set consists of a single uncontrolled still.