DocumentCode
2853368
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
fYear
2004
fDate
18-20 Dec. 2004
Firstpage
306
Lastpage
309
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Graphics (ICIG'04), Third International Conference on
Conference_Location
Hong Kong, China
Print_ISBN
0-7695-2244-0
Type
conf
DOI
10.1109/ICIG.2004.62
Filename
1410446
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