Fast and Effective Background Subtraction Based on eLBP

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	Fast and Effective Background Subtraction Based on eLBP
	Wang, Lingfeng; Pan, Chunhong
	2010
会议名称	International Conference on Acoustics,Speech, and Signal Processing
会议录名称	International Conference on Acoustics,Speech, and Signal Processing
会议日期	2010
会议地点	Dallas, Texas, USA
摘要	Background subtraction is an important component of many com-puter vision systems. In this paper, we present a fast and efficient texture-based method for background subtraction in a video se-quence. At first, a novel LBP (Local Binary Pattern) operator called εLBP is applied to extract the local description of each pixel. Then, the kernel of background subtraction is performed based on two principle phases, i.e. the background building phase and the fore-ground detection phase. In the former phase, the probability that a pixel belongs to foreground is calculated based on the difference between the current εLBP and the adaptive mean εLBP. In the later phase, a thresholding operator is applied on the probability to determine whether a pixel can be classified as foreground, and the adaptive mean εLBP is updated by a user-settable learning rate. Finally, our approach is evaluated against several video sequences compared with the traditional MoG model. Experiments show that our method is suitable for various scenes and is appealing with respect to robustness.
关键词	Background Subtraction ε Lbp
语种	英语
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/10766
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习
作者单位	中国科学院自动化研究所
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Wang, Lingfeng,Pan, Chunhong. Fast and Effective Background Subtraction Based on eLBP[C],2010.

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