Title :
Kernel Non-Locality Preserving Projection and Its Application to Face Recognition
Author :
Wang, Jianguo ; Yang, Wankou ; Yan, Hui
Author_Institution :
Dept. of Comput. Sci. & Technol., Tangshan Coll., Tangshan, China
Abstract :
Non-locality preserving projection (NLPP) is a kind of feature extraction technique based on the characterization of the non-local scatter. Due to NLPP is a linear algorithm in nature, it cannot address nonlinear problem in recognition, so a novel subspace method, called Kernel Non-locality Preserving Projection (KNLPP) discriminant analysis, is proposed for face recognition. Experimental results on two popular benchmark databases, FERET and Yale, demonstrate the effectiveness of the proposed method.
Keywords :
face recognition; feature extraction; FERET; KNLPP discriminant analysis; Yale; benchmark databases; face recognition; feature extraction technique; kernel nonlocality preserving projection; linear algorithm; nonlocal scatter; subspace method; Application software; Computer science; Data mining; Face recognition; Feature extraction; Image databases; Kernel; Laplace equations; Scattering; Spatial databases;
Conference_Titel :
Pattern Recognition, 2009. CCPR 2009. Chinese Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4199-0
DOI :
10.1109/CCPR.2009.5344046
