Background Subtraction Using Multiscale Fully Convolutional Network

doi:10.1109/access.2018.2817129

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	Background Subtraction Using Multiscale Fully Convolutional Network
	Zeng, D. D.; Zhu, M.
	2018
发表期刊	Ieee Access
ISSN	2169-3536
卷号	6 页码:16010-16021
摘要	Background modeling and subtraction based on change detection are the first step in many high-level computer vision applications. Many background subtraction methods have been proposed in the recent past and their efforts mainly focus on two aspects: more advanced background models and more complex feature representations. Recently, hierarchical features learned from deep convolutional neural networks have been shown to be effective for many computer vision tasks, such as classification and recognition. However, few researchers try to learn the deep features to address the background subtraction problem. Therefore, in this paper, we propose a novel multiscale fully convolutional network (MFCN) architecture which takes advantage of different layer features for background subtraction. We show that the foreground detection accuracy can be greatly improved by using the deep features learned from the MFCN and instead of building highly complex background models, and the complexity of the background subtraction process can be easily solved during the subtraction operation itself. Experimental results on CDnet 2014 data set and SBM-RGBD data set show that the proposed MFCN-based method achieves state-of-the-art performance while operating at real time.
关键词	Background subtraction convolutional neural network multiscale fully convolutional network video surveillance density-estimation Computer Science Engineering Telecommunications
DOI	10.1109/access.2018.2817129
收录类别	SCI ; EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/60914
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	Zeng, D. D.,Zhu, M.. Background Subtraction Using Multiscale Fully Convolutional Network[J]. Ieee Access,2018,6:16010-16021.
APA	Zeng, D. D.,&Zhu, M..(2018).Background Subtraction Using Multiscale Fully Convolutional Network.Ieee Access,6,16010-16021.
MLA	Zeng, D. D.,et al."Background Subtraction Using Multiscale Fully Convolutional Network".Ieee Access 6(2018):16010-16021.

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