Extended scale invariant local binary pattern for background subtraction

doi:10.1049/iet-ipr.2016.1026

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	Extended scale invariant local binary pattern for background subtraction
	Zeng, D. D.; Zhu, M.; Xu, F.; Zhou, T. X.
刊名	Iet Image Processing
	2018
卷号	12 期号:8 页码:1292-1302
关键词	visual surveillance density-estimation segmentation objects scenes model Computer Science Engineering Imaging Science & Photographic Technology
ISSN号	1751-9659
DOI	10.1049/iet-ipr.2016.1026
英文摘要	Background subtraction based on change detection is the first step in many video surveillance systems, an effective background subtraction algorithm should distinguish foreground from the background sensitively, and adapt to the variation of background scenes robustly. In this study, the authors propose a robust background subtraction algorithm which takes advantages of local texture features represented by an extended scale invariant local binary pattern and colour intensities to characterise pixel representations. Local texture features achieve good tolerance against illumination variations in rich texture regions but not so efficiently on uniform regions, so a photometric invariant colour measurement is proposed to overcome its limitation. Both quantitative and qualitative evaluations carried out on a well- known change detection dataset are provided to demonstrate the effectiveness of the proposed algorithm.
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/60989]
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	Zeng, D. D.,Zhu, M.,Xu, F.,et al. Extended scale invariant local binary pattern for background subtraction[J]. Iet Image Processing,2018,12(8):1292-1302.
APA	Zeng, D. D.,Zhu, M.,Xu, F.,&Zhou, T. X..(2018).Extended scale invariant local binary pattern for background subtraction.Iet Image Processing,12(8),1292-1302.
MLA	Zeng, D. D.,et al."Extended scale invariant local binary pattern for background subtraction".Iet Image Processing 12.8(2018):1292-1302.