A MANOVA of Major Factors of RIU-LBP Feature for Face Recognition

Author

Luo, Jie ; Fang, Yuchun ; Cai, Qiyun

Author_Institution

Sch. of Comput. Eng. & Sci., Shanghai Univ., Shanghai, China

fYear

2010

fDate

23-26 Aug. 2010

Firstpage

1028

Lastpage

1031

Abstract

Local Binary Patterns (LBP) feature is one of the most popular representation schemes for face recognition. The four factors deciding its effect are the blocking number, image resolution, the sampling radius and sampling density of LBP operator. Numerous previous researches have taken various groups of value of these factors based on experimental comparisons. However, which factor among them contributes the most? Numerous revisions are made to the LBP operators for it is believed that the LBP coding is the most essential factor. Is it true? In this paper, with the very simple and classical Multivariate Analysis of Variance (MANOVA), we discover that the blocking number contributes the most; though all four factors have significant effect for recognition rate. In addition, with the same analysis, we disclose the detailed effect of each factor and their interactions to the precision of LBP features.

Keywords

face recognition; feature extraction; image resolution; LBP; MANOVA; RIU-LBP Feature; blocking number; face recognition; image resolution; local binary patterns; multivariate analysis of variance; Binary codes; Face; Face recognition; Histograms; Image resolution; Pixel; Face Recognition; Local Bianry Pattern; MANOVA; RIU-LBP; face recogntiion;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition (ICPR), 2010 20th International Conference on

Conference_Location

Istanbul

ISSN

1051-4651

Print_ISBN

978-1-4244-7542-1

Type

conf

DOI

10.1109/ICPR.2010.257

Filename

5595851