Pixelwise Deep Sequence Learning for Moving Object Detection

doi:10.1109/TCSVT.2017.2770319

	Pixelwise Deep Sequence Learning for Moving Object Detection
	Chen, Yingying; Wang, Jinqiao; Zhu, Bingke; Tang, Ming; Lu, Hanqing
刊名	IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
	2019-09-01
卷号	29 期号:9 页码:2567-2579
关键词	Moving object detection background modeling moving object proposal convolutional neural networks
ISSN号	1051-8215
DOI	10.1109/TCSVT.2017.2770319
通讯作者	Wang, Jinqiao(jqwang@nlpr.ia.ac.cn)
英文摘要	Moving object detection is an essential, well-studied but still open problem in computer vision and plays a fundamental role in many applications. Traditional approaches usually reconstruct background images with hand-crafted visual features, such as color, texture, and edge. Due to lack of prior knowledge or semantic information, it is difficult to deal with complicated and rapid changing scenes. To exploit the temporal structure of the pixel-level semantic information, in this paper, we propose an end-to-end deep sequence learning architecture for moving object detection. First, the video sequences are input into a deep convolutional encoder-decoder network for extracting pixel-wise semantic features. Then, to exploit the temporal context, we propose a novel attention long short-term memory (Attention ConvLSTM) to model pixelwise changes over time. A spatial transformer network and a conditional random field layer are finally appended to reduce the sensitivity to camera motion and smooth the foreground boundaries. A multi-task loss is proposed to jointly optimization for frame-based classification and temporal prediction in an end-to-end network. Experimental results on CDnet 2014 and LASIESTA show 12.15% and 16.71% improvement to the state of the art, respectively.
资助项目	National Natural Science Foundation of China[61772527] ; National Natural Science Foundation of China[61375035]
WOS研究方向	Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000489738900004
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/26597]
专题	中国科学院自动化研究所
通讯作者	Wang, Jinqiao
作者单位	Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Chen, Yingying,Wang, Jinqiao,Zhu, Bingke,et al. Pixelwise Deep Sequence Learning for Moving Object Detection[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2019,29(9):2567-2579.
APA	Chen, Yingying,Wang, Jinqiao,Zhu, Bingke,Tang, Ming,&Lu, Hanqing.(2019).Pixelwise Deep Sequence Learning for Moving Object Detection.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,29(9),2567-2579.
MLA	Chen, Yingying,et al."Pixelwise Deep Sequence Learning for Moving Object Detection".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 29.9(2019):2567-2579.