(MCD)-C-4: A Robust Change Detection Method for Intelligent Visual Surveillance
Wang, Kunfeng1,2; Gou, Chao1; Wang, Fei-Yue1,3
Source PublicationIEEE ACCESS
AbstractIn this paper, we propose a robust change detection method for intelligent visual surveillance. This method, named (MCD)-C-4, includes three major steps. First, a sample-based background model that integrates color and texture cues is built and updated over time. Second, multiple heterogeneous features (including brightness variation, chromaticity variation, and texture variation) are extracted by comparing the input frame with the background model, and a multi-view learning strategy is designed to online estimate the probability distributions for both foreground and background. The three features are approximately conditionally independent, making multi-view learning feasible. Pixel-wise foreground posteriors are then estimated with Bayes rule. Finally, the Markov random field (MRF) optimization and heuristic postprocessing techniques are used sequentially to improve accuracy. In particular, a two-layer MRF model is constructed to represent pixel-based and superpixel-based contextual constraints compactly. Experimental results on the CDnet dataset indicate that (MCD)-C-4 is robust under complex environments and ranks among the top methods.
KeywordChange Detection Multimodal Background Multi-view Learning Conditional Independence Markov Random Field
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding OrganizationNational Natural Science Foundation of China(61533019 ; 71232006 ; 91720000)
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000429256000001
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Cited Times:20[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Qingdao Acad Intelligent Ind, Innovat Ctr Parallel Vis, Qingdao 266000, Peoples R China
3.Natl Univ Def Technol, Res Ctr Computat Expt & Parallel Sys, Changsha 410073, Hunan, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wang, Kunfeng,Gou, Chao,Wang, Fei-Yue. (MCD)-C-4: A Robust Change Detection Method for Intelligent Visual Surveillance[J]. IEEE ACCESS,2018,6:15505-15520.
APA Wang, Kunfeng,Gou, Chao,&Wang, Fei-Yue.(2018).(MCD)-C-4: A Robust Change Detection Method for Intelligent Visual Surveillance.IEEE ACCESS,6,15505-15520.
MLA Wang, Kunfeng,et al."(MCD)-C-4: A Robust Change Detection Method for Intelligent Visual Surveillance".IEEE ACCESS 6(2018):15505-15520.
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