DocumentCode
2171328
Title
An Improved Texture-Based Method for Background Subtraction Using Local Binary Patterns
Author
Tian, Guodong ; Men, Aidong
Author_Institution
Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear
2009
fDate
17-19 Oct. 2009
Firstpage
1
Lastpage
4
Abstract
Texture-based method (TBM) using local binary patterns (LBP) proposed in the work of Heikkila et al. (2004) is a successful solution to background subtraction especially for dynamic background scenes. However, it usually suffers from inaccuracy of the shapes of segmentation results and slow adaptation to the current situation. In this paper, we present an improved TBM that solves the two problems. To solve the first problem, a spatially weighted LBP histogram (SWLH) is proposed to be the feature vector and a simple shadow removing method is introduced. When dealing with the second one, we use an adaptive learning rate for each model LBP histogram and maintain multiple frame level models to process sudden illumination changes. Experimental results show that the proposed method outperforms the original TBM.
Keywords
image segmentation; image texture; adaptive learning rate; background subtraction; dynamic background scenes; illumination change; image segmentation; local binary patterns; shadow removing; spatially weighted LBP histogram; texture-based method; Computer vision; Convergence; Equations; Histograms; Layout; Lighting; Object detection; Shape; Switches; Video sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location
Tianjin
Print_ISBN
978-1-4244-4129-7
Electronic_ISBN
978-1-4244-4131-0
Type
conf
DOI
10.1109/CISP.2009.5304682
Filename
5304682
Link To Document