CASIA OpenIR  > 模式识别国家重点实验室  > 先进数据分析与学习
Adaptive eLBP for Background Subtraction
LingFeng Wang; Huai-Yu Wu; Chunhong Pan
2010
Conference NameThe Asian Conference on Computer Vision (ACCV 2010)
Source PublicationThe Asian Conference on Computer Vision (ACCV 2010)
Conference Date2010
Conference PlaceQueenstown, New Zealand
Abstract
Background subtraction plays an important role in many
computer vision systems, yet in complex scenes it is still a challenging
task, especially in case of illumination variations. In this work, we develop
an efficient texture-based method to tackle this problem. First,
we propose a novel adaptive εLBP operator, in which the threshold is
adaptively calculated by compromising two criterions, i.e. the description
stability and the discriminative ability. Then, the naive Bayesian technique
is adopted to effectively model the probability distribution of local
patterns in the pixel level, which utilizes only one single εLBP pattern
instead of εLBP histogram of local region. Our approach is evaluated
on several video sequences against the traditional methods. Experiments
show that our method is suitable for various scenes, especially can robust
handle illumination variations.
KeywordAdaptive Elbp For Background Subtraction
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12144
Collection模式识别国家重点实验室_先进数据分析与学习
Corresponding AuthorHuai-Yu Wu
AffiliationNLPR, CASIA
Recommended Citation
GB/T 7714
LingFeng Wang,Huai-Yu Wu,Chunhong Pan. Adaptive eLBP for Background Subtraction[C],2010.
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