Face Recognition Grand Challenge: The FRGC is structured around challenge problems that are designed to challenge researchers to meet the FRGC performance goal. There are three aspects of the FRGC that will be new to the face recognition community. The first aspect is the size of the FRGC in terms of data. The FRGC data set contains 50,000 recordings. The second aspect is the complexity of the FRGC. Previous face recognition data sets have been restricted to still images. The FRGC will consist of three modes: high resolution still images, 3D images, and multi-images of a person. The third new aspect is the infrastructure. The infrastructure for FRGC will be provided by the Biometric Experimentation Environment (BEE), an XML based framework for describing and documenting computational experiments. The BEE will allow the description and distribution of experiments in a common format, recording of the raw results of an experiment in a common format, analysis and presentation of the raw results in a common format, and documentation of the experiment format in a common format. This is the first time that a computational-experimental environment has supported a challenge problem in face recognition or biometrics.