DocumentCode :
2440296
Title :
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
Link To Document :
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