The goal of the Face Recognition Grand Challenge (FRGC) is to improve the performance of face recognition algorithms by an order of magnitude over the best results in Face Recognition Vendor Test (FRVT) 2002. The FRGC is designed to achieve this performance goal by presenting to researches a six-experiment challenge problem along with a data corpus of 50,000 images. The data consists of 3D scans and high resolution still imagery taken under controlled and uncontrolled conditions. This paper presents preliminary results of the FRGC for all six experiments. The preliminary results indicate that significant progress has been made towards achieving the stated goals.
Citation: NIST Interagency/Internal Report (NISTIR) - 7307
NIST Pub Series: NIST Interagency/Internal Report (NISTIR)
Pub Type: NIST Pubs
biometrics, evaluation, face recognition, generalized linear models, linear models