TY - GEN
T1 - NFRAD
T2 - 2011 International Joint Conference on Biometrics, IJCB 2011
AU - Maeng, Hyunju
AU - Choi, Hyun Cheol
AU - Park, Unsang
AU - Lee, Seong Whan
AU - Jain, Anil K.
PY - 2011
Y1 - 2011
N2 - Face recognition at a distance is gaining wide attention in order to augment the surveillance systems with face recognition capability. However, face recognition at a distance in nighttime has not yet received adequate attention considering the increased security threats at nighttime. We introduce a new face image database, called Near-Infrared Face Recognition at a Distance Database (NFRAD-DB). Images in NFRAD-DB are collected at a distance of up to 60 meters with 50 different subjects using a near-infrared camera, a telescope, and near-infrared illuminator. We provide face recognition performance using FaceVACS, DoG-SIFT, and DoG-MLBP representations. The face recognition test consisted of NIR images of these 50 subjects at 60 meters as probe and visible images at 1 meter with additional mug shot images of 10,000 subjects as gallery. Rank-1 identification accuracy of 28 percent was achieved from the proposed method compared to 18 percent rank-1 accuracy of a state of the art face recognition system, FaceVACS. These recognition results are encouraging given this challenging matching problem due to the illumination pattern and insufficient brightness in NFRAD images.
AB - Face recognition at a distance is gaining wide attention in order to augment the surveillance systems with face recognition capability. However, face recognition at a distance in nighttime has not yet received adequate attention considering the increased security threats at nighttime. We introduce a new face image database, called Near-Infrared Face Recognition at a Distance Database (NFRAD-DB). Images in NFRAD-DB are collected at a distance of up to 60 meters with 50 different subjects using a near-infrared camera, a telescope, and near-infrared illuminator. We provide face recognition performance using FaceVACS, DoG-SIFT, and DoG-MLBP representations. The face recognition test consisted of NIR images of these 50 subjects at 60 meters as probe and visible images at 1 meter with additional mug shot images of 10,000 subjects as gallery. Rank-1 identification accuracy of 28 percent was achieved from the proposed method compared to 18 percent rank-1 accuracy of a state of the art face recognition system, FaceVACS. These recognition results are encouraging given this challenging matching problem due to the illumination pattern and insufficient brightness in NFRAD images.
UR - http://www.scopus.com/inward/record.url?scp=84862946880&partnerID=8YFLogxK
U2 - 10.1109/IJCB.2011.6117486
DO - 10.1109/IJCB.2011.6117486
M3 - Conference contribution
AN - SCOPUS:84862946880
SN - 9781457713583
T3 - 2011 International Joint Conference on Biometrics, IJCB 2011
BT - 2011 International Joint Conference on Biometrics, IJCB 2011
Y2 - 11 October 2011 through 13 October 2011
ER -