A group of facial normal descriptors for recognizing 3D identical twins

Huibin Li, Di Huang, Liming Chen, Yunhong Wang, Jean-Marie Morvan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

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.
Original languageEnglish (US)
Title of host publication2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages271-277
Number of pages7
ISBN (Print)9781467313841
DOIs
StatePublished - Sep 2012

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