中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Background Subtraction Using Multiscale Fully Convolutional Network

文献类型:期刊论文

作者Zeng, D. D.; Zhu, M.
刊名Ieee Access
出版日期2018
卷号6页码:16010-16021
关键词Background subtraction convolutional neural network multiscale fully convolutional network video surveillance density-estimation Computer Science Engineering Telecommunications
ISSN号2169-3536
DOI10.1109/access.2018.2817129
英文摘要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.
源URL[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
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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.

入库方式: OAI收割

来源:长春光学精密机械与物理研究所

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