Please use this identifier to cite or link to this item:
|Title:||Surveillance video processing using compressive sensing|
|Keywords:||Alternating direction method|
Lowrank and sparse decomposition
|Citation:||Jiang, H., Deng, W., Shen, Z. (2012). Surveillance video processing using compressive sensing. Inverse Problems and Imaging 6 (2) : 201-214. ScholarBank@NUS Repository. https://doi.org/10.3934/ipi.2012.6.201|
|Abstract:||A compressive sensing method combined with decomposition of a matrix formed with image frames of a surveillance video into low rank and sparse matrices is proposed to segment the background and extract moving objects in a surveillance video. The video is acquired by compressive measurements, and the measurements are used to reconstruct the video by a low rank and sparse decomposition of matrix. The low rank component represents the background, and the sparse component is used to identify moving objects in the surveillance video. The decomposition is performed by an augmented Lagrangian alternating direction method. Experiments are carried out to demonstrate that moving objects can be reliably extracted with a small amount of measurements. © 2012 American Institute of Mathematical Sciences.|
|Source Title:||Inverse Problems and Imaging|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jul 13, 2018
WEB OF SCIENCETM
checked on Jun 12, 2018
checked on Apr 20, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.