Advanced Local Binary Pattern Descriptors for Crowd Estimation

Author

Ma, Wenhua ; Huang, Lei ; Liu, Changping

Author_Institution

Inst. of Autom., Chinese Acad. of Sci., Beijing

Volume

2

fYear

2008

fDate

19-20 Dec. 2008

Firstpage

958

Lastpage

962

Abstract

Local binary pattern (LBP) is a powerful texture descriptor that is gray-scale and rotation invariant. In this paper, an extension of the original LBP is proposed. LBP operator is adopted in multi-layer block domain, instead of pixel domain. Meanwhile, feature dimension is effectively reduced by dual-histogram LBP (DH-LBP). Combining merits of the two, we propose the advanced LBP (ALBP) and use that in solving the practical problem of crowd estimation. Experiment results demonstrate the performance and the potential of our method.

Keywords

feature extraction; image classification; image texture; statistical analysis; traffic engineering computing; advanced local binary pattern descriptor; crowd estimation; dual histogram; feature dimension; gray-scale invariant texture descriptor; image classification; multilayer block domain; rotation invariant texture descriptor; Automation; Computational intelligence; Computer industry; Conferences; Gray-scale; Histograms; Image edge detection; Image segmentation; Pattern recognition; Pixel; LBP; crowd estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3490-9

Type

conf

DOI

10.1109/PACIIA.2008.258

Filename

4756918