CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
A unified model sharing framework for moving object detection
Chen, Yingying1; Wang, Jinqiao1; Xu, Min2; He, Xiangjian2; Lu, Hanqing1
AbstractMillions of surveillance cameras have been installed in public areas, producing vast amounts of video data every day. It is an urgent need to develop intelligent techniques to automatically detect and segment moving objects which have wide applications. Various approaches have been developed for moving object detection based on background modeling in the literature. Most of them focus on temporal information but partly or totally ignore spatial information, bringing about sensitivity to noise and background motion. In this paper, we propose a unified model sharing framework for moving object detection. To begin with, to exploit the spatial-temporal correlation across different pixels, we establish a many-to-one correspondence by model sharing between pixels, and a pixel is labeled into foreground or background by searching an optimal matched model in the neighborhood. Then a random sampling strategy is introduced for online update of the shared models. In this way, we can reduce the total number of models dramatically and match a proper model for each pixel accurately. Furthermore, existing approaches can be naturally embedded into the proposed sharing framework. Two popular approaches, statistical model and sample consensus model, are used to verify the effectiveness. Experiments and comparisons on ChangeDetection benchmark 2014 demonstrate the superiority of the model sharing solution. (C) 2015 Elsevier B.V. All rights reserved.
KeywordMoving Object Detection Background Subtraction Shared Model
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding Organization863 Program(2014AA015104) ; National Natural Science Foundation of China(61273034 ; 61332016)
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000373538100009
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Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Corresponding AuthorWang, Jinqiao
Affiliation1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
2.Global Big Data Technologies Centre,University of Technology
Recommended Citation
GB/T 7714
Chen, Yingying,Wang, Jinqiao,Xu, Min,et al. A unified model sharing framework for moving object detection[J]. SIGNAL PROCESSING,2016(124):72-80.
APA Chen, Yingying,Wang, Jinqiao,Xu, Min,He, Xiangjian,&Lu, Hanqing.(2016).A unified model sharing framework for moving object detection.SIGNAL PROCESSING(124),72-80.
MLA Chen, Yingying,et al."A unified model sharing framework for moving object detection".SIGNAL PROCESSING .124(2016):72-80.
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