DocumentCode :
3601179
Title :
Foreground–Background Separation From Video Clips via Motion-Assisted Matrix Restoration
Author :
Xinchen Ye ; Jingyu Yang ; Xin Sun ; Kun Li ; Chunping Hou ; Yao Wang
Author_Institution :
Sch. of Electron. Inf. Eng., Tianjin Univ., Tianjin, China
Volume :
25
Issue :
11
fYear :
2015
Firstpage :
1721
Lastpage :
1734
Abstract :
Separation of video clips into foreground and background components is a useful and important technique, making recognition, classification, and scene analysis more efficient. In this paper, we propose a motion-assisted matrix restoration (MAMR) model for foreground-background separation in video clips. In the proposed MAMR model, the backgrounds across frames are modeled by a low-rank matrix, while the foreground objects are modeled by a sparse matrix. To facilitate efficient foreground-background separation, a dense motion field is estimated for each frame, and mapped into a weighting matrix which indicates the likelihood that each pixel belongs to the background. Anchor frames are selected in the dense motion estimation to overcome the difficulty of detecting slowly moving objects and camouflages. In addition, we extend our model to a robust MAMR model against noise for practical applications. Evaluations on challenging datasets demonstrate that our method outperforms many other state-of-the-art methods, and is versatile for a wide range of surveillance videos.
Keywords :
image motion analysis; image recognition; matrix algebra; video signal processing; video surveillance; anchor frame; foreground-background separation; low rank matrix; motion assisted matrix restoration; sparse matrix; video clips; video surveillance; weighting matrix; Adaptation models; Educational institutions; Lighting; Noise; Principal component analysis; Robustness; Sparse matrices; Background segmentation/subtraction; matrix restoration; motion detection; optical flow; video surveillance;
fLanguage :
English
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
1051-8215
Type :
jour
DOI :
10.1109/TCSVT.2015.2392491
Filename :
7014298
Link To Document :
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