A Novel Geometric Facial Representation based on Multi-Scale Extended Local Binary Patterns

Di Huang 1 Mohsen Ardabilian 1 Yunhong Wang Liming Chen 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : In this study, we present a novel geometric representation for 3D faces in order to enhance distinctiveness of generally smooth range images. This novel face representation is based on Multi-Scale Extended Local Binary Patterns (ELBP) and enables accurate and fast description of local shape variations on range faces. When associated with the proposed SIFT-based local feature matching scheme, this novel geometric facial representation shows its discriminative power in 3D face recognition, displaying a rank-one recognition rate up to 97.2% and a verification rate of 98.4% at a 0.001 FAR respectively on the FRGC v2.0 database. Moreover, costly registration is not needed thanks to the relative tolerance of the proposed representation and the SIFT methodology to moderate pose changes as the ones existing in FRGC v2.0. Finally, additional experiments demonstrate that the entire system is also robust to facial expression variations.
Document type :
Conference papers
Complete list of metadatas
https://hal.archives-ouvertes.fr/hal-01354380
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Thursday, August 18, 2016 - 7:24:53 PM
Last modification on : Wednesday, November 20, 2019 - 3:00:31 AM

Identifiers

Collections

CNRS | EC-LYON | UNIV-LYON2 | LIRIS | INSA-LYON | UNIV-LYON1 | INSA-GROUPE | LABEXIMU | UDL

Citation

Di Huang, Mohsen Ardabilian, Yunhong Wang, Liming Chen. A Novel Geometric Facial Representation based on Multi-Scale Extended Local Binary Patterns. IEEE International Conference on Automatic Face and Gesture Recognition (FG), Mar 2016, Santa Barbara, CA, United States. pp.1-7, ⟨10.1109/FG.2011.5771323⟩. ⟨hal-01354380⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

203

Contact

Informations

CCSD