TY - GEN
T1 - A group of facial normal descriptors for recognizing 3D identical twins
AU - Li, Huibin
AU - Huang, Di
AU - Chen, Liming
AU - Wang, Yunhong
AU - Morvan, Jean-Marie
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2012/9
Y1 - 2012/9
N2 - In this paper, to characterize and distinguish identical twins, three popular texture descriptors: i.e. local binary patterns (LBPs), gabor filters (GFs) and local gabor binary patterns (LGBPs) are employed to encode the normal components (x, y and z) of the 3D facial surfaces of identical twins respectively. A group of facial normal descriptors are thus achieved, including Normal Local Binary Patterns descriptor (N-LBPs), Normal Gabor Filters descriptor (N-GFs) and Normal Local Gabor Binary Patterns descriptor (N-LGBPs). All these normal encoding based descriptors are further fed into sparse representation classifier (SRC) for identification. Experimental results on the 3D TEC database demonstrate that these proposed normal encoding based descriptors are very discriminative and efficient, achieving comparable performance to the best of state-of-the-art algorithms. © 2012 IEEE.
AB - In this paper, to characterize and distinguish identical twins, three popular texture descriptors: i.e. local binary patterns (LBPs), gabor filters (GFs) and local gabor binary patterns (LGBPs) are employed to encode the normal components (x, y and z) of the 3D facial surfaces of identical twins respectively. A group of facial normal descriptors are thus achieved, including Normal Local Binary Patterns descriptor (N-LBPs), Normal Gabor Filters descriptor (N-GFs) and Normal Local Gabor Binary Patterns descriptor (N-LGBPs). All these normal encoding based descriptors are further fed into sparse representation classifier (SRC) for identification. Experimental results on the 3D TEC database demonstrate that these proposed normal encoding based descriptors are very discriminative and efficient, achieving comparable performance to the best of state-of-the-art algorithms. © 2012 IEEE.
UR - http://hdl.handle.net/10754/564603
UR - http://ieeexplore.ieee.org/document/6374588/
UR - http://www.scopus.com/inward/record.url?scp=84871999668&partnerID=8YFLogxK
U2 - 10.1109/BTAS.2012.6374588
DO - 10.1109/BTAS.2012.6374588
M3 - Conference contribution
SN - 9781467313841
SP - 271
EP - 277
BT - 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -