Video Foreground Detection via Sparse Representation
In this article we propose a novel background model method based on sparse representation theory. In this framework the image is divided into N N non-overlapping blocks, each block of a new input image has a sparse representation in the space spanned by background model. The sparse representation is achieved by solving an l1-regularized least squares problem which is computed by the preconditioned conjugate gradients (PCG) algorithm. Then the block with large error vector is taken as the foreground region. The experimental results show that proposed algorithm produces more accurate and stable results.
LIU Shuangshuang WANG Bo ZHENG Zhihui
School of Automation, Beijing Institute of Technology, Beijing 100081, P.R.China
国际会议
The 30th Chinese Control Conference(第三十届中国控制会议)
烟台
英文
1-5
2011-07-01（万方平台首次上网日期，不代表论文的发表时间）