A unified model sharing framework for moving object detection

doi:10.1016/j.sigpro.2015.10.011

	A unified model sharing framework for moving object detection
	Chen, Yingying1 ; Wang, Jinqiao1 ; Xu, Min 2; He, Xiangjian 2; Lu, Hanqing1
发表期刊	SIGNAL PROCESSING
	2016-07-01
期号	124 页码:72-80
文章类型	Article
摘要	Millions 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.
关键词	Moving Object Detection Background Subtraction Shared Model
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.sigpro.2015.10.011
关键词[WOS]	MULTILABEL IMAGE CLASSIFICATION
收录类别	SCI
语种	英语
项目资助者	863 Program(2014AA015104) ; National Natural Science Foundation of China(61273034 ; 61332016)
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000373538100009
引用统计	被引频次：11[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/11074
专题	紫东太初大模型研究中心_图像与视频分析
通讯作者	Wang, Jinqiao
作者单位	1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.Global Big Data Technologies Centre,University of Technology
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 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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