Title :
Face detection using improved LBP under Bayesian framework
Author :
Jin, Hongliang ; Liu, Qingshan ; Lu, Hanqing ; Tong, Xiaofeng
Author_Institution :
Nat. Lab of Pattern Recognition, Chinese Acad. of Sci., Beijing, China
Abstract :
In this paper, we present a novel face detection approach using improved local binary patterns (ILBP) as facial representation. ILBP feature is an improvement of LBP feature that considers both local shape and texture information instead of raw grayscale information and it is robust to illumination variation. We model the face and non-face class using multivariable Gaussian model and classify them under Bayesian framework. Extensive experiments show that the proposed method has an encouraging performance.
Keywords :
Bayes methods; Gaussian processes; face recognition; image representation; image texture; Bayesian framework; face detection; facial representation; improved local binary pattern; multivariable Gaussian model; raw grayscale information; texture information; Automation; Bayesian methods; Face detection; Facial features; Gray-scale; Lighting; Pattern recognition; Robustness; Shape; Support vector machines;
Conference_Titel :
Image and Graphics (ICIG'04), Third International Conference on
Conference_Location :
Hong Kong, China
Print_ISBN :
0-7695-2244-0
DOI :
10.1109/ICIG.2004.62