Surveillance video coding via low-rank and sparse decomposition

Chongyu Chen, Jianfei Cai, Weisi Lin, Guangming Shi

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

24 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationMM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery (ACM)
Pages713-716
Number of pages4
ISBN (Print)9781450310895
DOIs
Publication statusPublished - 2012
Externally publishedYes
EventACM International Conference on Multimedia 2012 - Nara, Japan
Duration: 29 Oct 20122 Nov 2012
Conference number: 20th
https://dl.acm.org/doi/proceedings/10.1145/2393347

Conference

ConferenceACM International Conference on Multimedia 2012
Abbreviated titleMM 2012
CountryJapan
CityNara
Period29/10/122/11/12
OtherProceedings of the 20th ACM international conference on Multimedia
Internet address

Keywords

  • cur decomposition
  • low-rank and sparse decomposition
  • surveillance video compression

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