Abstract
Videos captured by stationary cameras are usually with a static or gradually changed background. Existing schemes are not able to globally exploit the strong background temporal redundancy. In this paper, motivated by the recent advance on low-rank and sparse decomposition (LRSD), we propose to apply it for the compression of videos captured by fixed cameras. In particular, the LRSD is employed to decompose the input video into the low-rank component, representing the background, and the sparse component, representing the moving objects, which are encoded by different methods. Moreover, we further propose an incremental LRSD (ILRSD) algorithm to reduce the large memory requirement and high computational complexity of the existing LRSD algorithm, which facilitates the process of large-scale video sequences without much performance loss. Experimental results show that the proposed coding scheme can significantly improve the existing standard codecs, H.264/AVC and HEVC, and outperform the state-of-the-art background modeling based coding schemes.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Visual Communication and Image Representation
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
