Adaptive texture-color based background subtraction for video surveillance

Texture and color are two primitive forms of features that can be used to describe a scene. While conventional local binary pattern (LBP) texture based background subtraction performs well on texture rich regions, it fails to detect uniform foreground objects in large uniform background. As such, co...

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Bibliographic Details
Main Authors: Teck Wee Chua, Yue Wang, Leman, K.
Format: Conference Proceeding
Language:English
Subjects:
Adaptation models
adaptive weight
Background subtraction
color
Computational modeling
Heuristic algorithms
Histograms
Image color analysis
Indexes
local binary pattern
texture
Video surveillance
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Description
Summary:Texture and color are two primitive forms of features that can be used to describe a scene. While conventional local binary pattern (LBP) texture based background subtraction performs well on texture rich regions, it fails to detect uniform foreground objects in large uniform background. As such, color information can be used to complement texture feature. In this study, we propose to incorporate local color feature based on Improved Hue, Luminance, and Saturation (IHLS) color space and introduce an adaptive scheme that automatically adjusts the weight between texture and color similarities based on the pixel's local properties: texture uniformity and color saturation. Experiments on eight challenging sequences demonstrate the effectiveness of the proposed method compared to the state-of-the-art algorithms.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2012.6466792