Relative-Error $CUR$ Matrix Decompositions
SIAM Journal on Matrix Analysis and Applications
A Singular Value Thresholding Algorithm for Matrix Completion
SIAM Journal on Optimization
H.263: video coding for low-bit-rate communication
IEEE Communications Magazine
Overview of the H.264/AVC video coding standard
IEEE Transactions on Circuits and Systems for Video Technology
Motion matters: a novel framework for compressing surveillance videos
Proceedings of the 21st ACM international conference on Multimedia
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Surveillance videos are usually with a static or gradually changed background. The state-of-the-art block-based codec, H.264/AVC, is not sufficiently efficient for encoding surveillance videos since it cannot exploit the strong background temporal redundancy in a global manner. In this paper, motivated by the recent advance on low-rank and sparse decomposition (LRSD), we propose to apply it for the compression of surveillance videos. In particular, the LRSD is employed to decompose a surveillance video into the low-rank component, representing the background, and the sparse component, representing the moving objects. Then, we design different coding methods for the two different components. We represent the frames of the background by very few independent frames based on their linear dependency, which dramatically removes the temporal redundancy. Experimental results show that, for the compression of surveillance videos, the proposed scheme can significantly outperform H.264/AVC, up to 3 dB PSNR gain, especially at relatively low bit rates.