Title :
Face Recognition with Locally Linear Embedding on Local Binary Patterns
Author :
Cai, Lin-bo ; Ying, Zi-lu
Author_Institution :
Sch. of Inf., Wuyi Univ., Jiangmen, China
Abstract :
In this paper, A new approach to face recognition is constructed by combining the local binary pattern (LBP) operator and locally linear embedding (LLE). LBP is an effective low-cost image descriptor to extract facial texture feature which represents the local structure of face images. LLE is an excellent non-linear data dimensionality reduction method. Its main optimization only involves a sparse eigenvalue problem and do not involves local minima. The new approach benefits from the advantages of both LBP and LLE. The proposed algorithm is experimented on ORL database. Extensive experiments are carried out to compare with other common methods such as LDA and LLE. The experiment results show that the combination of LBP+LLE provides better performance than that of those traditional algorithms and prove the effectiveness of the proposed algorithm.
Keywords :
eigenvalues and eigenfunctions; face recognition; feature extraction; image representation; image texture; ORL database; face recognition; facial texture feature extraction; image descriptor; local binary patterns; local structure representation; locally linear embedding; nonlinear data dimensionality reduction method; sparse eigenvalue problem; Binary codes; Data mining; Eigenvalues and eigenfunctions; Face recognition; Feature extraction; Image databases; Information science; Lighting; Pattern recognition; Pixel;
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
DOI :
10.1109/ICISE.2009.584